01-19-11 - Good practices

Some things that I always regret when I don't do them. These are as much reminders for myself not to get lazy as they are finger-wags at you all.

1. Save every log.

My programs generally log very verbosely. I log more to the file than to stdout. The key thing is that you shouldn't just overwrite your previous log. You should save every log of your runs *forever*. Disks are big, there is no reason to ever clean this up.

Your log file should contain the time & date of the run + the time & date of the build (this is mildly annoying to do in practice, just using __DATE__ somewhere in your code doesn't work because that module may not be fresh compiled). Ideally it would have the P4 sync state of the code as well (see comments). Ideally it would also log the modtime and/or checksum of every file that you take as input, so you can associate a run with the condition of the files it loads as well.

This is an okay way to start your logs :

// log the command line :
void lprintfCommandLine(int argc,char * argv[])
{
    for(int i=0;i < argc;i++)
    {
        lprintf("%s ",argv[i]);
    }
}

// log the command line + build time :
void lprintfLogHeader(const char * progName,int argc,char * argv[])
{
    __time64_t long_time;
    _time64( &long_time );
    
    lprintf("-----------------------------------------------------------------\n");
    // note: asctime has a \n in it already
    lprintf("Log opened : %s",asctime(_localtime64( &long_time )));
    lprintf("%s built %s, %s\n",progName,__DATE__,__TIME__);    
    lprintf("args: ");
    lprintfCommandLine(argc,argv);
    lprintf("\n");  
}

Something I've doing for a while now is to automatically write my logs to "c:\logs\programname.log" , and if a previous one of those exists I append it onto programname.prev . That's okay but not perfect, for one thing the big prev file gets hard to search through; perhaps worse, it doesn't play well with running multiple instances of your program at once (their logs get interleaved and the prev is moved at a random spot).

My videotest does something that I like even better. It makes a new log file for each run and names it by the date/time of the run and the command line args. They all go in a dir "c:\logs\programname\" and then the names are like "-c0rpjt1.rmv-irparkjoy_444_720p_lagarith_50.avi-p-d0-Sun-Jan-16-15-42-27-2011.log" which makes it very easy for me to find particular runs and see what the args were.

2. Make tests reproducable.

Often I'll run some tests and record the result, and then later when I go back to it I'm confused by what was run exactly, where the data files were, etc. Doing this is really just about discipline. There are a few things that I believe help :

2.A. Always make batch files. When you run command lines, do not just type in the command line and run it to execute your test. Put the command line in a batch file and run that. Then check your batch file into perforce!

2.B. Take the results of the test and write a quick note about how they were run and what they were testing. eg. exactly what #define did you flip in the code to run the test. It's so easy to not take this step because you think "its obvious" what you did, but 12 months later it won't be obvious. Check this into perforce.

2.C. For more interesting tests, make a directory and copy the whole thing! Copy in the data files that you ran on, the batch files, the results, and the code! Also copy in any tools you used! eg. if you used imagemagick or ffmpeg or whatever as part of your process, just copy it in to the directory. Disk is cheap and huge! Save the whole thing somewhere so you have a record of what exactly you ran.

2.D. If you changed code to run the test - check it in! Even if it's just for the test run - check in the test code and then check it in back to normal. eg. if you flip a #define or change some constants - check that in to P4 with a description saying "for test such and such".

(ASIDE : the first company I ever worked out was CTC in Houston. At CTC when we finished a major project, we would make an archive of the entire project and everything we needed to reproduce it. That means the code, the compilers, any tools or libraries, and the whole OS. We could take an archive and restore it to a fresh machine and instantly have a working system that would build it. I just thought that made a lot of sense and obviously every developer did that, right? Nope. I have yet to see anyone else do it since. People seem to believe that they can just archive the code without recording everything that needed to be done to the tools and build environment and so on to make a working build system.)

3. Never leave magic numbers in code.

I often stumble back on some old code and find something like :

x = y + 7 * z;

umm.. WTF where did that 7 come from? Even if you only use that value in one spot in the code, give it a name. eg.

const double c_averageACtoDCratio = 7;

x = y + c_averageACtoDCratio * z;

Ah, okay. Which is related to :

4. When values come from training or tweaking, document exactly how they were generated.

Ideally you saved the training run as per #2, so you should be able to just add a comment like

// this value comes from training; see train_averageACtoDCratio.bat

You may think you've found the perfect tweak value, but some day you may come back to it and think "where did this come from? am I sure this right? does this still apply since I've changed a bunch of other things since then?". Also, what data did you train it on exactly? Does that data actually reflect what you're using it for now?

Ideally ever value that comes from training can be regenerated at any time. Don't just do your training run and save the value and then break your training code. Assume that any tweak value will have to be regenerated in the future.

5. Some notes on default values.

In more complex programs, don't just put the default value of a parameter in its initializer, eg.

int maxNumMovecSearches = 32;

no no. The problem is that the initializer can be hidden away in a weird spot, and there may be multiple initializers, and you may want to reset values to their defaults, etc. Instead give it a proper name, like :

const int c_maxNumMovecSearches_default = 32;

int maxNumMovecSearches = c_maxNumMovecSearches_default;

Now you can also show defaults on the command line, such as :

lprintf("videotest usage:\n");
lprintf("-m# : max num movec searches [%d]\n",c_maxNumMovecSearches_default);

For args that are unclear what scale they're on, you should also show a reasonable parameter range, eg.

lprintf("-l# : lagrange lambda [%f] (0.1 - 1.0)\n",c_lagrangeLambda_default);

(though this example violates my own rule of baking constants into strings)

6. Make all options into proper enums with names.

You should never have a "case 2:" in your code or an "if ( mode == 1 )". Every time I short-cut and do that I wind up regretting it. For example I had some code doing :

SetupDCT(quantizer,6);

To select the 6th qtable. Of course that inevitably leads to bugs when I decide to reorder the qtables.

Give your enums the right name automatically using XX macros , eg. :

#define DCTQTableIndex_XX  \
    XX(eDctQ_Flat) YY(=0),\
    XX(eDctQ_Jpeg),\
    XX(eDctQ_JpegChroma),\
    XX(eDctQ_JpegFlattened),\
    XX(eDctQ_JpegSquashed),\
    XX(eDctQ_H264_HVS_1),\
    XX(eDctQ_H264_HVS_2),\
    XX(eDctQ_LerpedChroma),\
    XX(eDctQ_LerpedLuma),\
    XX(eDctQ_Count)

enum EDCTQTableIndex
{
    #define XX(x) x
    #define YY(y) y
    DCTQTableIndex_XX
    #undef XX
    #undef YY
};

const char * c_DCTQTableIndex_names[] =
{
    #define XX(x) #x
    #define YY(y)
    DCTQTableIndex_XX
    #undef XX
    #undef YY
};

And then make sure you echo the name when somebody selects an enum numerically so you can show that they are correct.

Do not keep a table of names and a table of enums that must be kept in sync manually. In general do not keep *anything* in code that must be kept in sync manually.

Show them as part of the command line help, eg :

        myprintf("imdiffs:\n");
        for(int f=0;f < eImDiff_Count;f++)
        {
            myprintf("%2d : %s\n",f,c_imDiffTypeNames[f]);
        }

For example if you tried to be a good boy and had something like :

    lprintf("dct qtable names:\n");
    lprintf("0: flat\n");
    lprintf("1: jpeg\n");
    ....

You have just "hard-coded" the values through the use of string constants. Don't bake in values.

One nice way is if command line arg "-m#" selects mode #, then "-m" with no arg should list the modes ("-m" followed by anything non-numeric should do the same).

If somebody has to go read the docs to use your program, then your command line user interface (CLUI) has failed. Furthermore docs are another example of bad non-self-maintaining redundancy. The list of arg mappings in the docs can get out of sync with the code : never rely on the human programmer to keep things in sync, make the code be correct automagically.

7. Copy the exe.

It's so easy during work to think of the exe as a temp/derivative item which you are replacing all the time, but you will often get yourself into scenarios where it's hard to get back to some old state and you want to play with the exe from that old state. So just copy off the exe every so often. Any time you generate major test results is a good time for this - output your CSV test files or whatever and just take a copy of the exe used to make the tests.

A semi-related practice that I've taken up now is to copy off the exe out of the build target location any time I run a test, so that I can still build new versions, and if I do build new versions, the version I wanted to test isn't fouled. eg. I use something like :

run_vt_test.bat :

  call zc -o release\vt.exe r:\vt_test.exe
  r:\vt_test.exe %*

8. Automate your processing

If you're running some process that requires a few steps - like run this exe, take the number it outputs, copy it into this code, recompile, run that on this data file - automate it.

It might seem like it's faster just to do it yourself than it is to automate it. That may in fact be true, but automating it has lots of ancillary value that makes it worth doing.

For one thing, it documents the process. Rather than just having to write a document that describes "how to export a character for the game" (which you will inevitably not write or not keep up to date), instead you have your batch file or script or whatever that does the steps.

For another, it gives you a record of what's being done and a way to exactly repeat the process if there are bugs. Any time you have a human step in the process it adds an element of non-repeatability and uncertainty, is this character broken because there's a bug or just because someone didn't follow the right steps?

There are some very simple ghetto tricks to easy automation. One is to have your program fwrite some text to a batch file and then just run that batch.

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More generally, I wish my computer kept a full journal of everything I ever did on it. Everything I type, the state of every file, everything run should be stored in a history which I can play back like a movie any time I want. I should just be able to go, "mmkay, restore to the condition of May 13, 2009 and play back from 3:15 to 3:30". Yeah, maybe that's a bit unrealistic, but it certainly is possible in certain limitted cases (eg. apps that don't access the net or take input from any weird drivers) which are the cases I mainly care about.

01-18-11 - Hadamard

The normal way the Hadamard Transform (Wikipedia) is written is not in frequency order like the DCT. For example the 8-item Hadamard as written on Wikipedia is :

    +1 +1 +1 +1 +1 +1 +1 +1
    +1 -1 +1 -1 +1 -1 +1 -1
    +1 +1 -1 -1 +1 +1 -1 -1
    +1 -1 -1 +1 +1 -1 -1 +1
    +1 +1 +1 +1 -1 -1 -1 -1
    +1 -1 +1 -1 -1 +1 -1 +1
    +1 +1 -1 -1 -1 -1 +1 +1
    +1 -1 -1 +1 -1 +1 +1 -1

The correct reordering is :

  { 0 7 3 4 1 6 2 5 }

When that's done what you get is :

    +1 +1 +1 +1 +1 +1 +1 +1
    +1 +1 +1 +1 -1 -1 -1 -1
    +1 +1 -1 -1 -1 -1 +1 +1
    +1 +1 -1 -1 +1 +1 -1 -1
    +1 -1 -1 +1 +1 -1 -1 +1
    +1 -1 -1 +1 -1 +1 +1 -1
    +1 -1 +1 -1 -1 +1 -1 +1
    +1 -1 +1 -1 +1 -1 +1 -1

which more closesly matches the DCT basis functions.

You can of course do the Hadamard transform directly like an 8x8 matrix multiply, but the faster way is to use a "fast hadamard transform" which is exactly analogous to a "fast fourier transform" - that is, you decompose it into a log(N) tree of two-item butterflies; this gives you 8*3 adds instead of 8*8. The difference is the Hadamard doesn't involve any multiplies, so all you need are {a+b,a-b} butterflies.

{
ADDENDUM : to be more concrete, fast hadamard is this :

    vec[0-7] = eight entries
    evens = vec[0,2,4,6]
    odds  = vec[1,3,5,7]

    Butterfly :
        vec[0-3] = evens + odds
        vec[4-7] = evens - odds

    Hadamard8 :
        Butterfly three times

this produces "canonical order" not frequency order, though obviously using a different shuffle in the final butterfly fixes that easily.
}

To do 2d , you obviously do the 1d Hadamard on rows and then on columns. The normalization factor for 1d is 1/sqrt(8) , so for 2d it's just 1/8 , or if you prefer the net normalization for forward + inverse is 1/64 and you can just apply it on either the forward or backward. The Hadamard is self-inverting (and swizzling rows doesn't change this).

The correctly ordered Hadamard acts on images very similarly to the DCT, though it compacts energy slightly less on most images, because the DCT is closer to the KLT of typical images.

In these examples I color code the 8x8 DCT or Hadamard entries. The (0,y) and (x,0) primary row and column are green. The (x,y) (x>0,y>0) AC entries are a gradient from blue to red, more red where vertical detail dominates and more blue where horizontal detail dominates. The brightness is the magnitude of the coefficient.

If you look at the two images, you should be able to see they are very similar, but Hadamard has more energy in the higher frequency AC bands.

original :

dct :

hadamard :

I also found this paper :

Designing Quantization Table for Hadamard Transform based on Human Visual System for Image Compression

which applies JPEG-style CSF design to make a quantization matrix for the Hadamard transform.

In straight C, the speed difference between Hadamard and DCT is not really super compelling. But Hadamard can be implemented very fast indeed with MMX or other SIMD instruction sets.

It seems that the idea of using the Hadamard as a rough approximation of the DCT for purposes of error or bit-rate estimation is a good one. It could be made even better by scaling down the high frequency AC components appropriately.

ADDENDUM : some more stats :

DCT :
root(L2) : 
+-------+-------+-------+-------+-------+-------+-------+-------+
|126.27 |  7.94 |  4.41 |  2.85 |  2.00 |  1.48 |  1.12 |  0.90 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  8.47 |  4.46 |  3.06 |  2.10 |  1.51 |  1.15 |  0.86 |  0.69 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  4.86 |  3.27 |  2.43 |  1.76 |  1.34 |  1.02 |  0.78 |  0.62 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  3.13 |  2.33 |  1.88 |  1.45 |  1.12 |  0.90 |  0.72 |  0.60 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  2.22 |  1.71 |  1.47 |  1.18 |  0.96 |  0.77 |  0.63 |  0.55 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  1.62 |  1.26 |  1.13 |  0.98 |  0.80 |  0.65 |  0.58 |  0.56 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  1.23 |  0.94 |  0.90 |  0.79 |  0.66 |  0.58 |  0.52 |  0.51 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  0.92 |  0.77 |  0.72 |  0.67 |  0.59 |  0.56 |  0.51 |  0.79 |
+-------+-------+-------+-------+-------+-------+-------+-------+

Hadamard :
root(L2) : 
+-------+-------+-------+-------+-------+-------+-------+-------+
|126.27 |  7.33 |  4.11 |  3.64 |  2.00 |  2.03 |  1.97 |  1.73 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  7.82 |  4.01 |  2.75 |  2.16 |  1.47 |  1.46 |  1.33 |  1.00 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  4.51 |  2.92 |  2.15 |  1.69 |  1.28 |  1.21 |  1.09 |  0.81 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  3.90 |  2.26 |  1.74 |  1.41 |  1.10 |  1.04 |  0.93 |  0.71 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  2.22 |  1.66 |  1.39 |  1.14 |  0.96 |  0.89 |  0.78 |  0.62 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  2.24 |  1.59 |  1.28 |  1.06 |  0.88 |  0.81 |  0.74 |  0.60 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  2.19 |  1.42 |  1.14 |  0.94 |  0.78 |  0.74 |  0.67 |  0.59 |
+-------+-------+-------+-------+-------+-------+-------+-------+
|  1.88 |  1.04 |  0.85 |  0.74 |  0.65 |  0.60 |  0.59 |  0.92 |
+-------+-------+-------+-------+-------+-------+-------+-------+

DCT :
FracZero : 
+-------+-------+-------+-------+-------+-------+-------+-------+
|  4.48 | 36.91 | 52.64 | 61.32 | 68.54 | 76.64 | 82.60 | 87.18 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 34.78 | 48.93 | 57.95 | 65.56 | 72.17 | 79.63 | 84.84 | 88.69 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 49.88 | 57.31 | 63.19 | 69.21 | 76.14 | 81.96 | 86.48 | 89.98 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 58.79 | 64.01 | 68.24 | 73.48 | 79.53 | 84.15 | 88.10 | 91.14 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 66.13 | 70.03 | 74.37 | 78.79 | 82.44 | 86.57 | 89.97 | 92.38 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 72.79 | 76.66 | 79.56 | 82.31 | 85.42 | 88.87 | 91.62 | 93.51 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 79.74 | 82.22 | 83.90 | 86.16 | 88.68 | 91.13 | 93.16 | 94.72 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 85.08 | 86.57 | 87.88 | 89.59 | 91.35 | 93.07 | 94.61 | 95.74 |
+-------+-------+-------+-------+-------+-------+-------+-------+

Hadamard :
FracZero : 
+-------+-------+-------+-------+-------+-------+-------+-------+
|  4.48 | 38.38 | 53.95 | 50.15 | 68.54 | 69.20 | 67.81 | 65.50 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 36.14 | 51.13 | 60.26 | 61.90 | 72.82 | 73.11 | 73.67 | 76.59 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 51.21 | 59.22 | 65.63 | 68.40 | 76.63 | 76.53 | 77.78 | 82.02 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 47.59 | 61.22 | 68.33 | 70.63 | 78.36 | 78.52 | 80.18 | 84.12 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 66.13 | 70.80 | 75.02 | 77.85 | 82.44 | 82.72 | 83.62 | 88.09 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 66.09 | 71.37 | 75.47 | 77.84 | 82.67 | 83.22 | 84.83 | 88.54 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 65.34 | 72.54 | 77.05 | 79.82 | 83.99 | 85.04 | 86.52 | 89.92 |
+-------+-------+-------+-------+-------+-------+-------+-------+
| 63.44 | 76.15 | 81.42 | 83.66 | 87.91 | 88.36 | 89.81 | 92.43 |
+-------+-------+-------+-------+-------+-------+-------+-------+

01-17-11 - ImDiff Release

Imdiff Win32 executables are now available for download. You can get them from my exe index page or direct link to zip download .

If you wish to link to imdiff, please link to this blog post as I will post updates here.

If you wish to run the JPEG example batch file, you may need to get JPEG exes here and get PackJPG here . Install them somewhere and set a dos environment variable "jpegpath" to where that is. Or modify the batch files to point at the right place. If you don't know how to use dos batch files, please don't complain to me, instead see here for example.

Once you have your JPEG installed correctly, you can just run "jpegtests image.bmp" and it will make nice charts like you've seen here.

I am not connected to those JPEG distributions in any way. Imdiff is not a JPEG tester. The JPEG test is just provided as an example. You should learn from the batch files and do something similar for whatever image compressor you wish to test.

ADDENDUM : See the Summary Post of all imdiff related blog posts.

01-12-11 - ImDiff Sample Run and JXR test

This is the output of a hands-off fully automatic run :

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(on lena 512x512 RGB ) :

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I was disturbed by how bad JPEG-XR was showing so I went and got the reference implementation from the ISO/ITU standardization committee and built it. It's here .

They provide VC2010 projects, which is annoying, but it built relatively easily in 2005.

Unfortunately, they just give you a bunch of options and not much guide on how to get the best quality for a given bit rate. Dear encoder writers : you should always provide a mode that gives "best rmse" or "best visual quality" for a given bit rate - possibly by optimizing your options. They also only load TIF and PNM ; dear encoder writers : you should prefer BMP, TGA and PNG. TIF is an abortion of an over-complex format (case in point : JXR actually writes invalid TIFs from its decoder (the tags are not sorted correctly)).

There are two ways to control bit-rate, either -F to throw away bit levels or -q to quantize. I tried both and found no difference in quality (except that -F mucks you up at high bit rate). Ideally the encoder would choose the optimal mix of -F and -q for R/D. I used their -d option to set UV quant from Y quant.

There are three colorspace options - y420,y422,y444. I tried them all. With no further ado :

Conclusions :

This JXR encoder is very slightly better than the MS one I was using previously, but doesn't differ significantly. It appears the one I was using previously was in YUV444 color space. Obviously Y444 gives you better RMSE behavior at high bitrate, but hurts perceptual scores.

Clearly the JXR encoders need some work. The good RMSE performance tells us it is not well perceptually optimized. However, even if it was perceptually optimized it is unlikely it would be competitive with the good coders. For example, Kakadu already matches it for RMSE, but kills it on all other metrics.

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BTW you may be asking "cbloom, why is it that plain old JPEG (jpg_h) tests so well for you, when other people have said that it's terrible?". Well, there are two main reasons. #1 is they use screwed up encoders like Photoshop that put thumbnails or huge headers in the JPEG. #2 and probably the main reason is that they test at -3 or even -4 logbpp , where jpg_h falls off the quality cliff because of the old-fashioned huffman back end. #3 is that they view the JPEG at some resolution other than 1:1 (under magnification of minification); any image format that is perceptually optimized must be encoded at the viewing resolution.

One of the ways you can get into that super-low-bitrate domain where JPEG falls apart is by using images that are excessively high resolution for your display, so that you are always scaling them down in display. The solution of course is to scale them down to viewing resolutions *before* encoding. (eg. lots of images on the web are actually 1600x1200 images, encoded at JPEG Q=20 or something very low, and then displayed on a web page at a size of 400x300 ; you would obviously get much better results by using a 400x300 image to begin with and encoding at higher quality).

01-10-11 - Perceptual Metrics

Almost done.

RMSE of fit vs. observed MOS data :

RMSE_RGB             : 1.052392
SCIELAB_RMSE         : 0.677143
SCIELAB_MyDelta      : 0.658017
MS_SSIM_Y            : 0.608917
MS_SSIM_IW_Y         : 0.555934
PSNRHVSM_Y           : 0.521825
PSNRHVST_Y           : 0.500940
PSNRHVST_YUV         : 0.480360
MyDctDelta_Y         : 0.476927
MyDctDelta_YUV       : 0.444007

BTW I don't actually use the raw RMSE as posted above. I bias by the sdev of the observed MOS data - that is, smaller sdev = you care about those points more. See previous blog posts on this issue. The sdev biased scores (which is what was posted in previous blog posts) are :

RMSE_RGB             : 1.165620
SCIELAB_RMSE         : 0.738835
SCIELAB_MyDelta      : 0.720852
MS_SSIM_Y            : 0.639153
MS_SSIM_IW_Y         : 0.563823
PSNRHVSM_Y           : 0.551926
PSNRHVST_Y           : 0.528873
PSNRHVST_YUV         : 0.515720
MyDctDelta_Y         : 0.490206
MyDctDelta_YUV       : 0.458081
Combo                : 0.436670 (*)

(* = ADDENDUM : I added "Combo" which is the best linear combo of SCIELAB_MyDelta + MS_SSIM_IW_Y + MyDctDelta_YUV ; it's a static linear combo, obviously you could do better by going all Netflix-Prize-style and treating each metric as an "expert" and doing weighted experts based on various decision attributes of the image; eg. certain metrics will do better on certain types of images so you weight them from that).

For sanity check I made plots (click for hi res) ; the X axis is the human observed MOS score, the Y axis is the fitted metric :

Sanity is confirmed. (the RMSE_RGB plot has those horizontal lines because one of the distortion types is RGB random noise at a few fixed RMSE levels - you can see that for the same amount of RGB RMSE noise there are a variety of human MOS scores).

ADDENDUM : if you haven't followed old posts, this is on the TID2008 database (without "exotics"). I really need to find another database to cross-check to make sure I haven't over-trained.

Some quick notes of what worked and what didn't work.

What worked :

Variance Masking of high-frequency detail

Variance Masking of DC deltas

PSNRHVS JPEG-style visibility thresholds

Using the right spatial scale for each piece of the metric
  (eg. what size window for local sdev, what spatial filter for DC delta)

Space-frequency subband energy preservation

Frequency subband weighting


What didn't work :

Luma Masking

LAB or other color spaces than YUV in most metrics

anything but "Y" as the most important part of the metric

Nonlinear mappings of signal and perception
  (other than the nonlinear mapping already in gamma correction)

01-10-11 - Perceptual Results - PDI

This is my 766x1200 version of the PDI test image (that I made by scaling down a 3600 tall jpeg one).

Hipix and JPEG-XR are both very bad. I wonder if the JPEG-XR encoder I'm using could be less than the best? If someone knows a reference to the best command line windows JPEG-XR encoder, please post it. The one I'm using is from some Microsoft HD-Photo SDK distribution.

It's interesting to see how the different encoders do on the different metrics. x264, webp and kakadu are all identical under MyDctDelta. Kakadu falls down in SSIM, but does much better on SCIELAB. This tells you that kakadu is not preserving local detail characteristics as well, but is preserving smooth overall DC levels much better.

01-10-11 - Perceptual Results - mysoup

Two sets of compressors cuz I have too many on this image ; jpg_pack is on both charts as a baseline.

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As before, we see AIC , Hipix and JPEG-XR are all very poor. WebP is marginally okay (the early encoder I'm using is still very primitive) ; it does well on SSIM, but doesn't have the good low bitrate behavior you would expect from a modern coder. x264 and Kakadu are quite good. My two coders (vtims and newdct) are better than the terrible trio but not close to the good ones (I need to fix my shit).

01-10-11 - Perceptual Results - Moses

Moses is a 1600x1600 photo of a guy.

01-10-11 - Perceptual Metrics Warmup - x264 Settings

Beginning the warmup. Quick guide to these charts :

On the left you will see either "err" or "fit". "err" is the raw score of the metric. "fit" is the metric after fitting to a 0-10 human visual quality scale. SSIM err is actually percent acos angle as usual.

The fit score is 0-10 for 0 = complete ass and 10 = perfect, but I have set the graph range to 3-8 , because that is the domain we normally care about. 8 = very hard to tell the difference.

x264 on mysoup , testing different "tune" options. I'm using my y4m to do the color convert for them which helps a lot.

Well "tune psnr" is in fact best on psnr - you can see a big difference on the RMSE chart. "tune ssim" doesn't seem to actually help much on SSIM, it only beats "tune psnr" at very low bit rate. "tune stillimage" just seems to be broken in my build of x264.

Oh, and I use "xx" to refer to x264 because I can't have numbers in the names of things.

Henceforth we will use tune = ssim. (change : psnr)

ADDENDUM :

I looked into this a little more on another image (also trying x264 with no explicit tune specified) :

You can see that "--tune ssim" does help a tiny bit on MS-SSIM , but it *hurts* IW-MS-SSIM , which is a better metric (it hurts also on MyDctDeltaNew). Though the differences are pretty negligible for our level of study. No explicit tune x264 is much worse. "tune psnr" seems to be the best option according to our best metrics.

01-10-11 - Perceptual Metrics Warmup - JPEG Settings

This is a repeat of old info, just warming up the new system and setting baselines.

Our JPEG is just regular old IJG JPEG with various lossless recompressors ; results on PDI :

As seen before, PAQ has some screwups at low bitrate but is otherwise very close to packjpg, and flat quantization matrix is obviously best for RMSE but worse for visual quality ("flat" here is flat + pack).

From now on we will use jpg_pack as the reference point.

01-05-11 - QuadraticExtremum

In today's story I do someone's homework for them :

/*
QuadraticExtremum gives you the extremum (either minimum or maximum)
of the quadratic that passes through the three points x0y0,x1y1,x2y2
*/
inline double QuadraticExtremum(
    double x0,double y0,
    double x1,double y1,
    double x2,double y2)
{   
    // warning : this form is pretty but it's numerically very bad
    //  when the three points are near each other
    
    double s2 = x2*x2;
    double s1 = x1*x1;
    double s0 = x0*x0;
    
    double numer = y0*(s1-s2) + y1*(s2-s0) + y2*(s0-s1);
    double denom = y0*(x1-x2) + y1*(x2-x0) + y2*(x0-x1);
    
    double ret = 0.5 * numer / denom;
    
    return ret;
}

01-05-11 - Golden 1d Searches

GoldenSearch1d finds the minimum of some function if you know the finite range to look in. Search1d_ExpandingThenGoldenDown looks in the infinite interval >= 0 . Pretty trivial thing, but handy.

The Golden ratio arises from doing a four point search and trying to reuse evaluations. If your four points are { 0, rho, 1-rho ,1 } and you shrink to the lower three { 0, rho, 1-rho }, then you want to reuse the rho evaluation as your new high interior point, so you require (1-rho)^2 = rho , hence 1-rho = (sqrt(5)-1)/2

BTW because you have various points you could obviously use interpolation search (either linear or quadratic) at various places here and reduce the number of evaluations needed to converge. See Brent's method or Dekker's method .

Also obviously this kind of stuff only works on functions with simple minima.

Also obviously if func is analytic and you can take derivatives of it there are better ways. I use this for evaluating things that aren't simple functions, but have nice shapes (such as running my image compressor with different quantizers).

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template< typename t_functor >  
double GoldenSearch1d( t_functor func, double lo, double v_lo, double hi, double v_hi, double minstep )
{
    const double rho = 0.381966;
    const double irho = 1.0 - rho; // = (sqrt(5)-1)/2 

    // four points :
    // [lo,m1,m2,hi]

    double m1 = irho*lo + rho*hi;
    double m2 = irho*hi + rho*lo;

    double v_m1 = func( m1 );
    double v_m2 = func( m2 );
    
    while( (m1-lo) > minstep )
    {
        // step to [lo,m1,m2] or [m1,m2,hi]
        // only one func eval per iteration :
        if ( MIN(v_lo,v_m1) < MIN(v_hi,v_m2) )
        {
            hi = m2; v_hi = v_m2;
            m2 = m1; v_m2 = v_m1;
            m1 = irho*lo + rho*hi;
            v_m1 = func( m1 );
        }
        else
        {
            lo = m1; v_lo = v_m1;
            m1 = m2; v_m1 = v_m2;
            m2 = irho*hi + rho*lo;
            v_m2 = func( m2 );
        }
        
        ASSERT( fequal(m2, irho*hi + rho*lo) );
        ASSERT( fequal(m1, irho*lo + rho*hi) );
    }
    
    // could do a cubic fit with the 4 samples I have now
    //  but they're close together so would be numerically unstable
    
    /*
    //return (lo+hi)/2.0;
    
    if ( v_m1 < v_m2 ) return m1;
    else return m2;
    
    /*/
    // return best of the 4 samples :
    if ( v_lo < v_m1 ) { v_m1 = v_lo; m1 = lo; }
    if ( v_hi < v_m2 ) { v_m2 = v_hi; m2 = hi; }
    
    if ( v_m1 < v_m2 ) return m1;
    else return m2;
    /**/
}

template< typename t_functor >  
double GoldenSearch1d( t_functor func, double lo, double hi, double minstep )
{
    double v_lo = func( lo );
    double v_hi = func( hi );
    
    return GoldenSearch1d( func, lo, v_lo, hi, v_hi, minstep );
}

template< typename t_functor >  
double Search1d_ExpandingThenGoldenDown( t_functor func, double start, double step, double minstep , const int min_steps = 8)
{
    struct Triple
    {
        double t0,f0;
        double t1,f1;
        double t2,f2;
    };
    
    Triple cur;
    cur.t2 = cur.t1 = cur.t0 = start;
    cur.f2 = cur.f1 = cur.f0 = func( start );
        
    int steps = 0;
    
    Triple best = cur;
    
    for(;;)
    {
        cur.t0 = cur.t1; 
        cur.f0 = cur.f1;
        cur.t1 = cur.t2; 
        cur.f1 = cur.f2;
        
        cur.t2 = cur.t1 + step;
        cur.f2 = func( cur.t2 );
        
        if ( cur.f1 <= best.f1 )
        {
            best = cur;
        }
        
        // if we got worst and we're past min_steps :
        if ( cur.f2 > cur.f1 && steps > min_steps )
            break;
                
        const double golden_growth = 1.618034; // 1/rho - 1
        step *= golden_growth; // grow step by some amount
        steps++;
    }
        
    // best is at t1 bracketed in [t0,t2]   
    // could save one function eval by passing in t1,f1 as well
    
    return GoldenSearch1d(func,best.t0,best.f0,best.t2,best.f2,minstep);
}

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Usage example :

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#define MAKE_FUNCTOR(type,func) \
struct STRING_JOIN(func,_functor) { \
  type operator() (type x) { return func(x); } \
};

double TFunc( double x )
{
    return 100 / ( x + 1) + x;
}

MAKE_FUNCTOR(double,TFunc);

int main(int argc,char *argv[])
{

double t = Search1d_ExpandingThenGoldenDown(TFunc_functor(),0.0,1.0,0.0001);

lprintfvar(t);
lprintf(TFunc(t) , "\n");

return 0;
}