Image analysis – Image compression or coding – Quantization
Reexamination Certificate
1998-03-06
2001-06-19
Boudreau, Leo (Department: 2721)
Image analysis
Image compression or coding
Quantization
C382S240000, C382S246000, C382S239000, C375S240110, C375S240190
Reexamination Certificate
active
06249614
ABSTRACT:
CROSS-REFERENCE TO RELATED APPLICATIONS
Not Applicable.
BACKGROUND OF THE INVENTION
1. Field of the Invention
The invention relates to the field of image data compression and decompression.
2. Background Information
Computer systems display both still and motion video images. Motion video usually consists of a sequence of images (referred to as frames) that, when displayed at a particular frame rate, will appear as “real-time” motion to a human eye. A still video image or a frame in a motion video sequence comprises a number of elements referred to as pixels (e.g., a 640×480 image comprises over 300,000 pixels). Each pixel is represented by a binary pattern that describes that pixel's characteristics (e.g., color, brightness, etc.). Given the number of pixels in a typical video image, storing and/or transmitting uncompressed still or motion video data requires a relatively large amount of computer storage space and/or bandwidth. Additionally, in several motion video applications, processing and displaying a sequence of frames must be performed fast enough to provide real-time motion (typically, between 15-30 frames per second). Techniques have been developed to compress the amount of data required to represent still and motion video, making it possible for more computing systems to process still and motion video.
One such compression technique is based on decomposing a frame into its different components using a digital filter, and then encoding each component using the coding technique best suited to that component's characteristics. To provide an example, subband coding in a technique by which each frame is decomposed into a number of frequency subbands, which are then encoded using the coding technique best suited to that subband's characteristics. As another example, various references describe different frame compression systems that are based on using wavelets to decompose a frame into its constituent components (e.g., U.S. Pat. No. 5,661,822; U.S. Pat. No. 5,600,373). For example, a frame compression system can decompose an image into a high frequency subband (H) and a low frequency subband (L), and then further decompose the H and L subbands to generate a high-high frequency part (HH), a high-low frequency part (HL), a low-high frequency part (LH), and a low-low frequency part (LL). Generally, the LL subband contains most of the signal energy, while the HH subband represents a relatively small percentage of the energy.
The results of the decomposition are typically quantized and encoded. While certain techniques have been described for quantizing and encoding the result of decomposed image data (U.S. Pat. No. 5,135,670; U.S. Pat. No. 5,412,741), lower processing complexity, higher quality, and/or higher compression ratio techniques are desired and/or required.
BRIEF SUMMARY OF THE INVENTION
A method and apparatus for performing video compression and decompression using dynamic quantization and/or encoding is described. According to one aspect of the compression method, an image is recursively filtered into its constituent components each represented by a matrix of coefficients. Next, the level of correlation of a first of the matrices of coefficients is determined. Based on the level of correlation of this first coefficient matrix, one of a first quantization technique and a second quantization technique is selected. The first coefficient matrix is then quantized using the selected quantization technique.
According to another aspect of the compression method, an image is digitally filtered into its constituent components, each represented by a matrix of coefficients. At least certain matrices are quantized to generated a first quantized matrix. The first quantized matrix is then recursively divided until the first quantized matrix or each of the resulting submatrices is sufficiently dense or sufficiently sparse. Each of the sufficiently dense matrices are encoded using a first technique, while each of the sufficiently sparse matrices are encoded a second technique.
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Bocharova Irina E.
Kolesnik Victor D.
Kudryashov Boris D.
Malkov Andrey
Marsavin Andrey
Alaris Inc.
Blakely & Sokoloff, Taylor & Zafman
Boudreau Leo
Sherali Ishrat
LandOfFree
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