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• Introducing WebM, an open web media project

  20 mai 2010, par noreply@blogger.com (christosap)

  A key factor in the web’s success is that its core technologies such as HTML, HTTP, TCP/IP, etc. are open and freely implementable. Though video is also now core to the web experience, there is unfortunately no open and free video format that is on par with the leading commercial choices. To that end, we are excited to introduce WebM, a broadly-backed community effort to develop a world-class media format for the open web.

  WebM includes :
  

  • VP8, a high-quality video codec we are releasing today under a BSD-style, royalty-free license
  • Vorbis, an already open source and broadly implemented audio codec
  • a container format based on a subset of the Matroska media container

  The team that created VP8 have been pioneers in video codec development for over a decade. VP8 delivers high quality video while efficiently adapting to the varying processing and bandwidth conditions found on today’s broad range of web-connected devices. VP8’s efficient bandwidth usage will mean lower serving costs for content publishers and high quality video for end-users. The codec’s relative simplicity makes it easy to integrate into existing environments and requires less manual tuning to produce high quality results. These existing attributes and the rapid innovation we expect through the open-development process make VP8 well suited for the unique requirements of video on the web.

  A developer preview of WebM and VP8, including source code, specs, and encoding tools is available today at www.webmproject.org.

  We want to thank the many industry leaders and web community members who are collaborating on the development of WebM and integrating it into their products. Check out what Mozilla, Opera, Google Chrome, Adobe, and many others below have to say about the importance of WebM to the future of web video.

  
  

  AMD

  ARM

  Brightcove

  Broadcom

  Collabora

  Digital Rapids

  Encoding.com

  Grab Networks

  iLinc

  INLET

  Kaltura

  Logitech

  MIPS

  Nvidia

  Ooyala

  Qualcomm

  Skype

  Sorenson

  Telestream
  

  Texas Instruments

  Verisilicon

  ViewCast

  Wildform

  
  

  Posted by Jeremy Doig, Engineering Director of video and Mike Jazayeri, Group Product Manager, Google

  

• IJG swings again, and misses

  1er février 2010, par Mans — Multimedia

  Earlier this month the IJG unleashed version 8 of its ubiquitous libjpeg library on the world. Eager to try out the “major breakthrough in image coding technology” promised in the README file accompanying v7, I downloaded the release. A glance at the README file suggests something major indeed is afoot :

  Version 8.0 is the first release of a new generation JPEG standard to overcome the limitations of the original JPEG specification.

  The text also hints at the existence of a document detailing these marvellous new features, and a Google search later a copy has found its way onto my monitor. As I read, however, my state of mind shifts from an initial excited curiosity, through bewilderment and disbelief, finally arriving at pure merriment.

  Already on the first page it becomes clear no new JPEG standard in fact exists. All we have is an unsolicited proposal sent to the ITU-T by members of the IJG. Realising that even the most brilliant of inventions must start off as mere proposals, I carry on reading. The summary informs me that I am about to witness the introduction of three extensions to the T.81 JPEG format :

  1. An alternative coefficient scan sequence for DCT coefficient serialization
  2. A SmartScale extension in the Start-Of-Scan (SOS) marker segment
  3. A Frame Offset definition in or in addition to the Start-Of-Frame (SOF) marker segment

  Together these three extensions will, it is promised, “bring DCT based JPEG back to the forefront of state-of-the-art image coding technologies.”

  Alternative scan

  The first of the proposed extensions introduces an alternative DCT coefficient scan sequence to be used in place of the zigzag scan employed in most block transform based codecs.

  

  Alternative scan sequence

  The advantage of this scan would be that combined with the existing progressive mode, it simplifies decoding of an initial low-resolution image which is enhanced through subsequent passes. The author of the document calls this scheme “image-pyramid/hierarchical multi-resolution coding.” It is not immediately obvious to me how this constitutes even a small advance in image coding technology.

  At this point I am beginning to suspect that our friend from the IJG has been trapped in a half-world between interlaced GIF images transmitted down noisy phone lines and today’s inferno of SVC, MVC, and other buzzwords.

  (Not so) SmartScale

  Disguised behind this camel-cased moniker we encounter a method which, we are told, will provide better image quality at high compression ratios. The author has combined two well-known (to us) properties in a (to him) clever way.

  The first property concerns the perceived impact of different types of distortion in an image. When encoding with JPEG, as the quantiser is increased, the decoded image becomes ever more blocky. At a certain point, a better subjective visual quality can be achieved by down-sampling the image before encoding it, thus allowing a lower quantiser to be used. If the decoded image is scaled back up to the original size, the unpleasant, blocky appearance is replaced with a smooth blur.

  The second property belongs to the DCT where, as we all know, the top-left (DC) coefficient is the average of the entire block, its neighbours represent the lowest frequency components etc. A top-left-aligned subset of the coefficient block thus represents a low-resolution version of the full block in the spatial domain.

  In his flash of genius, our hero came up with the idea of using the DCT for down-scaling the image. Unfortunately, he appears to possess precious little knowledge of sampling theory and human visual perception. Any block-based resampling will inevitably produce sharp artefacts along the block edges. The human visual system is particularly sensitive to sharp edges, so this is one of the most unwanted types of distortion in an encoded image.

  Despite the obvious flaws in this approach, I decided to give it a try. After all, the software is already written, allowing downscaling by factors of 8/8..16.

  Using a 1280×720 test image, I encoded it with each of the nine scaling options, from unity to half size, each time adjusting the quality parameter for a final encoded file size of no more than 200000 bytes. The following table presents the encoded file size, the libjpeg quality parameter used, and the SSIM metric for each of the images.

  Scale	Size	Quality	SSIM
  8/8	198462	59	0.940
  8/9	196337	70	0.936
  8/10	196133	79	0.934
  8/11	197179	84	0.927
  8/12	193872	89	0.915
  8/13	197153	92	0.914
  8/14	188334	94	0.899
  8/15	198911	96	0.886
  8/16	197190	97	0.869

  Although the smaller images allowed a higher quality setting to be used, the SSIM value drops significantly. Numbers may of course be misleading, but the images below speak for themselves. These are cut-outs from the full image, the original on the left, unscaled JPEG-compressed in the middle, and JPEG with 8/16 scaling to the right.

  

  

  Looking at these images, I do not need to hesitate before picking the JPEG variant I prefer.

  Frame offset

  The third and final extension proposed is quite simple and also quite pointless : a top-left cropping to be applied to the decoded image. The alleged utility of this feature would be to enable lossless cropping of a JPEG image. In a typical image workflow, however, JPEG is only used for the final published version, so the need for this feature appears quite far-fetched.

  The grand finale

  Throughout the text, the author makes references to “the fundamental DCT property for image representation.” In his own words :

  This property was found by the author during implementation of the new DCT scaling features and is after his belief one of the most important discoveries in digital image coding after releasing the JPEG standard in 1992.

  The secret is to be revealed in an annex to the main text. This annex quotes in full a post by the author to the comp.dsp Usenet group in a thread with the subject why DCT. Reading the entire thread proves quite amusing. A few excerpts follow.

  The actual reason is much simpler, and therefore apparently very difficult to recognize by complicated-thinking people.

  Here is the explanation :

  What are people doing when they have a bunch of images and want a quick preview ? They use thumbnails ! What are thumbnails ? Thumbnails are small downscaled versions of the original image ! If you want more details of the image, you can zoom in stepwise by enlarging (upscaling) the image.

  So with proper understanding of the fundamental DCT property, the MPEG folks could make their videos more scalable, but, as in the case of JPEG, they are unable to recognize this simple but basic property, unfortunately, and pursue rather inferior approaches in actual developments.

  These are just phrases, and they don’t explain anything. But this is typical for the current state in this field : The relevant people ignore and deny the true reasons, and thus they turn in a circle and no progress is being made.

  However, there are dark forces in action today which ignore and deny any fruitful advances in this field. That is the reason that we didn’t see any progress in JPEG for more than a decade, and as long as those forces dominate, we will see more confusion and less enlightenment. The truth is always simple, and the DCT *is* simple, but this fact is suppressed by established people who don’t want to lose their dubious position.

  I believe a trip to the Total Perspective Vortex may be in order. Perhaps his tin-foil hat will save him.

• Brute Force Dimensional Analysis

  15 juillet 2010, par Multimedia Mike — Game Hacking, Python

  I was poking at the data files of a really bad (is there any other kind ?) interactive movie video game known simply by one letter : D. The Sega Saturn version of the game is comprised primarily of Sega FILM/CPK files, about which I wrote the book. The second most prolific file type bears the extension ’.dg2’. Cursory examination of sample files revealed an apparently headerless format. Many of the video files are 288x144 in resolution. Multiplying that width by that height and then doubling it (as in, 2 bytes/pixel) yields 82944, which happens to be the size of a number of these DG2 files. Now, if only I had a tool that could take a suspected raw RGB file and convert it to a more standard image format.

  Here’s the FFmpeg conversion recipe I used :

   ffmpeg -f rawvideo -pix_fmt rgb555 -s 288x144 -i raw_file -y output.png
  

  So that covers the files that are suspected to be 288x144 in dimension. But what about other file sizes ? My brute force approach was to try all possible dimensions that would yield a particular file size. The Python code for performing this operation is listed at the end of this post.

  It’s interesting to view the progression as the script compresses to different sizes :

  
  
  

  That ’D’ is supposed to be red. So right away, we see that rgb555(le) is not the correct input format. Annoyingly, FFmpeg cannot handle rgb555be as a raw input format. But this little project worked well enough as a proof of concept.

  If you want to toy around with these files (and I know you do), I have uploaded a selection at : http://multimedia.cx/dg2/.

  Here is my quick Python script for converting one of these files to every acceptable resolution.

  work-out-resolution.py :
  

  PLAIN TEXT

  PYTHON :

  1. # !/usr/bin/python
  2.  
  3. import commands
  4. import math
  5. import os
  6. import sys
  7.  
  8. FFMPEG = "/path/to/ffmpeg"
  9.  
  10. def convert_file(width, height, filename) :
  11.  outfile = "%s-%dx%d.png" % (filename, width, height)
  12.  command = "%s -f rawvideo -pix_fmt rgb555 -s %dx%d -i %s -y %s" % (FFMPEG, width, height, filename, outfile)
  13.  commands.getstatusoutput(command)
  14.  
  15. if len(sys.argv) <2 :
  16.  print "USAGE : work-out-resolution.py <file>"
  17.  sys.exit(1)
  18.  
  19. filename = sys.argv[1]
  20. if not os.path.exists(filename) :
  21.  print filename + " does not exist"
  22.  sys.exit(1)
  23.  
  24. filesize = os.path.getsize(filename) / 2
  25.  
  26. limit = int(math.sqrt(filesize)) + 1
  27. for i in xrange(1, limit) :
  28.  if filesize % i == 0 and filesize & 1 == 0 :
  29.   convert_file(i, filesize / i, filename)
  30.   convert_file(filesize / i, i, filename)