Abstract:
A method for encoding at least one extra bit in an image compression and decompression system. The method includes accessing an input image, and compressing the input image into a compressed image using an encoder system, wherein said encoding system implements an algorithm for encoding at least one extra bit. The method further includes communicatively transferring the compressed image to a decoding system, and decompressing the compressed image into a resulting uncompressed image that is unaltered from said input image, wherein the algorithm for encoding enables the recovery of the at least one extra bit.

Description:
FIELD OF THE INVENTION 
     The present invention is generally related to computer systems. 
     BACKGROUND OF THE INVENTION 
     Entropy or lossless encoders include Lempel-Ziv encoders and are used for many different purposes. Discrete Cosine Transform (“DCT”) or JPEG-type compressors, allow users to select a level of image quality. With DCT, uncorrelated coefficients are produced so that each coefficient can be treated independently without loss of compression efficiency. The DCT coefficients can be quantized using visually-weighted quantization values which selectively discard the least important information. 
     DCT, however, suffers from a number of shortcomings. One problem with DCT and JPEG-type compressors is that they require usually bigger blocks of pixels, typically 8.times.8 or 16.times.16 pixels, as a minimally accessible unit in order to obtain a reasonable compression factor and quality. Access to a very small area, or even a single pixel involves fetching a large quantity of compressed data, thus requiring increased processor power and memory bandwidth. 
     Block truncation coding (“BTC”) and color cell compression (“CCC”) use a local one-bit quantizer on 4.times.4 pixel blocks. The compressed data for such a block consists of only two colors and 16-bits that indicate which one of the two colors is assigned to each of the 16 pixels. Decoding a BTC/CCC image consists of using a multiplexer with a look-up table so that once a 16-texel-block (32-bits) is retrieved from memory, the individual pixels are decoded by looking up the two possible colors for that block and selecting the color according to the associated bit from the 16 decision bits. 
     Therefore, there is a need for a method and system that maximizes the accuracy of compressed images while minimizing storage, memory bandwidth requirements, and decoding hardware complexities, while also compressing image data blocks into convenient sizes to maintain alignment for random access to any one or more pixels. 
     SUMMARY OF THE INVENTION 
     In one embodiment, the present invention is implement it as a method for encoding at least one extra bit in an image compression and decompression system. The method includes accessing an input image, and compressing the input image into a compressed image using an encoder system, wherein said encoding system implements an algorithm for encoding at least one extra bit. The method further includes communicatively transferring the compressed image to a decoding system, and decompressing the compressed image into a resulting uncompressed image that is unaltered from said input image, wherein the algorithm for encoding enables the recovery of the at least one extra bit. 
     The foregoing is a summary and thus contains, by necessity, simplifications, generalizations and omissions of detail; consequently, those skilled in the art will appreciate that the summary is illustrative only and is not intended to be in any way limiting. Other aspects, inventive features, and advantages of the present invention, as defined solely by the claims, will become apparent in the non-limiting detailed description set forth below. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements. 
         FIG. 1  shows an algorithm illustrating the general form of an algorithm in accordance with one embodiment of the present invention. 
         FIG. 2  shows a truth image for the function F(x,y) for n=8 in accordance with one embodiment of the present invention. 
         FIG. 3  shows a truth image for a function in accordance with one embodiment of the present invention. 
         FIG. 4  shows a truth image for a function in accordance with one embodiment of the present invention. 
         FIG. 5  shows a truth image for a function in accordance with one embodiment of the present invention. 
         FIG. 6  shows six additional truth images for functions in accordance with one embodiment of the present invention. 
         FIG. 7  shows an image processing system in accordance with one embodiment of the present invention. 
         FIG. 8  shows a computer system in accordance with one embodiment of the present invention. 
         FIG. 9  shows an exemplary Linear-time generalization diagram in accordance with one embodiment of the present invention. 
         FIG. 10  shows an exemplary logarithmic-time generalization diagram in accordance with one embodiment of the present invention. 
         FIG. 11  shows an exemplary diagram depicting how a linear time generalization uses a lookup table to read in more than one bit at a time and reduce the number of stages required in accordance with one embodiment of the present invention. 
         FIG. 12  shows six exemplary truth images in accordance with one embodiment of the present invention. 
         FIG. 13  shows a code block of an exemplary computer program that is used to generate the truth images depicted above in accordance with one embodiment of the present invention. 
         FIG. 14  shows a code block of an exemplary computer program that is used to generate the truth images depicted above in accordance with one embodiment of the present invention. 
         FIG. 15  shows a code block of an exemplary computer program that is used to generate the truth images depicted above in accordance with one embodiment of the present invention. 
         FIG. 16  shows a code block of an exemplary computer program that is used to generate the truth images depicted above in accordance with one embodiment of the present invention. 
         FIG. 17  shows a code block of an exemplary computer program that is used to generate the truth images depicted above in accordance with one embodiment of the present invention. 
         FIG. 18  shows a code block of an exemplary computer program that is used to generate the truth images depicted above in accordance with one embodiment of the present invention. 
         FIG. 19  shows a code block of an exemplary computer program that is used to generate the truth images depicted above in accordance with one embodiment of the present invention. 
     
    
    
     DETAILED DESCRIPTION OF THE INVENTION 
     Reference will now be made in detail to the preferred embodiments of the present invention, examples of which are illustrated in the accompanying drawings. While the invention will be described in conjunction with the preferred embodiments, it will be understood that they are not intended to limit the invention to these embodiments. On the contrary, the invention is intended to cover alternatives, modifications and equivalents, which may be included within the spirit and scope of the invention as defined by the appended claims. Furthermore, in the following detailed description of embodiments of the present invention, numerous specific details are set forth in order to provide a thorough understanding of the present invention. However, it will be recognized by one of ordinary skill in the art that the present invention may be practiced without these specific details. In other instances, well-known methods, procedures, components, and circuits have not been described in detail as not to unnecessarily obscure aspects of the embodiments of the present invention. 
     Notation and Nomenclature: 
     Some portions of the detailed descriptions, which follow, are presented in terms of procedures, steps, logic blocks, processing, and other symbolic representations of operations on data bits within a computer memory. These descriptions and representations are the means used by those skilled in the data processing arts to most effectively convey the substance of their work to others skilled in the art. A procedure, computer executed step, logic block, process, etc., is here, and generally, conceived to be a self-consistent sequence of steps or instructions leading to a desired result. The steps are those requiring physical manipulations of physical quantities. Usually, though not necessarily, these quantities take the form of non-transitory electrical or magnetic signals capable of being stored, transferred, combined, compared, and otherwise manipulated in a computer readable storage medium of a computer system. It has proven convenient at times, principally for reasons of common usage, to refer to these signals as bits, values, elements, symbols, characters, terms, numbers, or the like. 
     It should be borne in mind, however, that all of these and similar terms are to be associated with the appropriate physical quantities and are merely convenient labels applied to these quantities. Unless specifically stated otherwise as apparent from the following discussions, it is appreciated that throughout the present invention, discussions utilizing terms such as “processing” or “accessing” or “executing” or “storing” or “rendering” or the like, refer to the action and processes of a computer system, or similar electronic computing device, that manipulates and transforms data represented as physical (electronic) quantities within the computer system&#39;s registers and memories into other data similarly represented as physical quantities within the computer system memories or registers or other such information storage, transmission or display devices. 
     Embodiments of the present invention implement an image encoding function for compressing image data, and through such compressing is able to encode one or more extra bits with the compressed image data such that the resulting decompressed image data is unaltered and the one or more extra bits are recovered by the decoder. In one embodiment, the present invention is implemented as an image processing system includes an image encoder system and an image decoder system that are coupled together. 
     Embodiments of the present invention includes functionality whereby the encoding format can be changed without altering the outcome of the decompressed image. The manner in which the encoding format is changed allows the encoding of at least one extra bit. The at least one extra bits enables an increase in precision in the encoding format. 
     In this manner, embodiments of the present invention can take advantage of the bit ordering in x and y in order to encode at least one extra bit. The extra bits can be used for a number of different applications in addition to increasing precision. The extra bits are gained at very little extra cost with respect to system hardware. The extra bits are extracted during the decoding process by the decoder. For tile-based image rendering implementations, for each tile, at least one extra bit can be obtained. 
     It should be noted that the term “image” as used herein comprises a multi-dimensional array of numbers that can represent an image, a function, a normal map, or any other collection of data. 
     In one embodiment, in the cases where we have two n-bit (unsigned) values (say, x and y) that can be swapped arbitrarily, we can encode an extra bit of information by applying a function F to x and y such that:
     1. F(x,y) returns 0 or 1.   2. F(x,y)=1−F(y,x) if x !=y.   3. F(x,x) can return either 0 or 1.   

     One example of such a function is F(x,y):=(x&lt;y). 
     For example, one way to implement (x&lt;y) is to subtract and look at the sign bit of (y−x). A much more compact implementation is to scan the bit representation from the least to the most significant bit and return a result. 
       FIG. 1  shows an algorithm  100  illustrating the general form of an algorithm in accordance with one embodiment of the present invention. The algorithm  100  presents an example that shows how each stage takes one bit each from x and y and the output of the previous stage, and passes one bit to the next stage. The value of truth, 0xD4, gives a result identical to F(x,y):=(x&lt;y). 
       FIG. 2  shows a truth image for the function F(x,y) for n=8 and all x and y in the range 0.255 (x is the horizontal axis, y the vertical; (x,y)=(0,0) is at the lower left.) Light grey is where F(x,y) is 1 and black is where F(x,y) is 0. 
       FIG. 3 ,  FIG. 4  and  FIG. 5  show three other values for truth and give similar images and implement the indicated function in the labels. 
       FIG. 6  shows six additional exemplary truth images in accordance with one embodiment of the present invention. Surprisingly, there are twelve other functions, however, that exist and satisfy the requirements. The truth tables (e.g., truth images) for six of them are shown in  FIG. 6 . The other six have the 0x100 bit set in their truth table. 
     It should also be noted that one can permute the bits of x and y and get other functions that work. For example, G(x,y):=F(permute(x), permute(y)) will also work and give very different truth images. However, arguably that is a small transformation and may not really give a different function, only a different interpretation of the same function. Additionally, it should be noted that the same permutation has to be applied to x and y. None of the twelve new functions above can be changed into an x&lt;y or x&gt;y form via permuting the input; thus, they are truly new and different functions. 
       FIG. 7  shows an image processing system  700  in accordance with one embodiment of the present invention. As described above, the image processing system includes an image encoder system that is communicatively coupled to an image decoder system. Embodiments of the present invention includes functionality whereby the encoding format can be changed without altering the outcome of the decompressed image. The manner in which the encoding format is changed allows the encoding of at least one extra bit. 
     Computer System Platform: 
       FIG. 8  shows a computer system  800  in accordance with one embodiment of the present invention. Computer system  800  depicts the components of a basic computer system in accordance with embodiments of the present invention providing the execution platform for certain hardware-based and software-based functionality. In general, computer system  800  comprises at least one CPU  801 , a system memory  815 , and at least one graphics processor unit (GPU)  810 . The CPU  801  can be coupled to the system memory  815  via a bridge component/memory controller (not shown) or can be directly coupled to the system memory  815  via a memory controller (not shown) internal to the CPU  801 . The GPU  810  is coupled to a display  812 . The GPU  810  is shown including image processing system  700 . One or more additional GPUs can optionally be coupled to system  800  to further increase its computational power. The GPU(s)  810  is coupled to the CPU  801  and the system memory  815 . System  800  can be implemented as, for example, a desktop computer system or server computer system, having a powerful general-purpose CPU  801  coupled to a dedicated graphics rendering GPU  810 . In such an embodiment, components can be included that add peripheral buses, specialized graphics memory, 10 devices, and the like. Similarly, system  800  can be implemented as a handheld device (e.g., cellphone, etc.) or a set-top video game console device such as, for example, the Xbox®, available from Microsoft Corporation of Redmond, Wash., or the PlayStation3®, available from Sony Computer Entertainment Corporation of Tokyo, Japan. 
     It should be appreciated that the GPU  810  can be implemented as a discrete component, a discrete graphics card designed to couple to the computer system  800  via a connector (e.g., AGP slot, PCI-Express slot, etc.), a discrete integrated circuit die (e.g., mounted directly on a motherboard), or as an integrated GPU included within the integrated circuit die of a computer system chipset component (not shown). Additionally, a local graphics memory  814  can be included for the GPU  810  for high bandwidth graphics data storage. 
     Generalization Embodiments of Functions that can be Used to Encode an Extra Bit: 
     In the above descriptions it has been demonstrated that are six new functions that satisfy f(x,y)=1−f(y,x) for x !=y. The description of the figures below will generalize the construction of the functions and provide many more examples of such functions. 
       FIG. 9  shows an exemplary Linear-time generalization diagram in accordance with one embodiment of the present invention. Here, we generalize f(x, y) with the structure shown in  FIG. 9  (assuming 8 bits to simplify the presentation). Each stage gn takes 1 bit from the previous stage and k≧1 successive bits from X and Y and computes 1 bit using a truth table, which is then passed on to the next stage. Identical or different truth tables can be used at each stage. Additionally, the bits in X and Y can be permuted identically prior to being loaded into the X and Y registers above. 
       FIG. 10  shows an exemplary logarithmic-time generalization diagram in accordance with one embodiment of the present invention. In the  FIG. 10  example, there are two separate sets of truth tables. A first function, Fn takes two 1-bit inputs and returns a 3-state output, while a second function, fn takes two 3-state inputs and returns a 3-state output. The 3 states are 0, 1, and ?, effectively (e.g., that is, f(x,x) will return“?”.). 
       FIG. 11  shows an exemplary diagram depicting how a linear time generalization uses a lookup table to read in more than one bit at a time and reduce the number of stages required in accordance with one embodiment of the present invention. As depicted in  FIG. 11 , to takes two k-bit inputs and returns either a 2-state or 3-state output. If there is only tO, then it is sufficient for the table to return a 2-state output. Otherwise it returns a 3-state result which is then fed to the next stage(s), which take two 3-state inputs and return a 3-state output. For a table tO only with two 4 bit inputs (thus the table is 16×16), there are 2 120  possible tables that satisfy the f(x,y)=1−f(y,x) relationship. 
       FIG. 12  shows six exemplary truth images in accordance with one embodiment of the present invention. Each image below represents a possible f(x,y). The term x is the horizontal axis, the term y the vertical, with (x,y)=(0,0) at the lower left. Black is f(x,y)==0, and light grey is f(x,y)==1. f(x,x) is shown a solid line. 
       FIG. 13-19  show code blocks of an exemplary computer program that is used to generate the truth images depicted above in accordance with one embodiment of the present invention. The computer program begins with code block  130  of  FIG. 13  and proceeds through code block  190  of  FIG. 19 . 
     The foregoing descriptions of specific embodiments of the present invention have been presented for purposes of illustration and description. They are not intended to be exhaustive or to limit the invention to the precise forms disclosed, and many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and its practical application, to thereby enable others skilled in the art to best utilize the invention and various embodiments with various modifications as are suited to the particular use contemplated. It is intended that the scope of the invention be defined by the claims appended hereto and their equivalents.