to illustrate compression of a video frame according to one representative embodiment , reference is made to fig1 . the process flow of fig1 begins at step 101 . in step 101 , a set of non - overlapping macroblocks of pixels are defined . the macroblocks may be subdivided into subblocks of size 16 × 16 , 16 × 8 , 8 × 16 , 8 × 8 , 4 × 8 , 4 × 4 , and / or the like in the manner disclosed by multiple block - size motion estimation . the different patterns of subdivision may be applied to respective macroblocks . also , the subdivision may vary on a frame by frame basis . each macroblock may include more than one component or channel ( e . g ., rgb , yiq , yuv , ycbcr , etc ). in step 102 , for each block within the current frame , a best - matching block is obtained . each best - matching block may be identified from a block of the same size in a reference frame . alternatively , the best - matching block may originate from a larger block in a manner similar to overlapping motion estimation . moreover , each best - matching block may be identified from a weighted linear combination of adjacent blocks in a manner similar to sub - pixel motion estimation or overlapping motion estimation / compensation algorithms . the weights applied to the multiple blocks to generate a best - matching block may vary on a pixel by pixel basis . also , the best - matching block may be identified from a combination of previous frames within a predefined distance and subsequent frames with a predefined distance . in one embodiment , the search for best - matching blocks for the blocks within frame i may traverse frames i − 2 , i − 1 , i + 1 , i + 2 and any blocks therein . the identification of the best - matching block may also use the current frame . furthermore , a respective best - matching block may be formed using a repetition of selected pixels in a manner similar to extended motion estimation . as an example , steps 101 and 102 may be performed using standard video processing algorithms such as the algorithms defined in the various mpeg compression standards . in step 103 , for each block in the current frame , an analysis of its corresponding best matching block is performed . the analysis may involve calculation of a conventional residual frame . the analysis may also include performing a respective sum of absolute differences calculation for each residual block , determining the energy in each residual block , analyzing the motion vector associated with each residual block , examining the past frame history of such characteristics , and / or the like . in step 104 , an optimal residual frame is calculated as a function of one or several variables ( e . g ., optimal_residual = function_f ( conventional_residual , one or several other parameters ). in one embodiment , a transform function of the selected parameter ( s ) associated with each block of the conventional residual frame is employed . the transform function is evaluated for each data element in the conventional residual frame and each data element in the residual frame is scaled by the resulting value . after each data element has been scaled , the conventional residual frame has been converted into the optimal residual frame . multiple functions may also be employed to generate a single optimal residual frame . the functions may be linear or non - linear . each function is selected to differentiate between signal information that is useful to the perceived quality of the data and signal information that is not important ( such as errors , noise , artifacts , and / or the like ). also , the functions may take many forms and / or formats . for example , suppose the compression algorithm is applied to video taken according to a slow motion “ drag ” of the camera . a low complexity function can be applied . alternatively , when a scene possesses more complex camera movements and object movements , a more complex function can be used to decide what information in the residual can be discarded ( or equivalently what is the best residual frame that can be produced given computational , resource , and time constraints ). the optimal reference frame differs from known residual frames in that the optimal reference frame does not encode all differences . specifically , the application of the transform function ( s ) removes information that is not important to the perceived quality of the data . accordingly , a greater amount of compression can be achieved . in step 105 , typical residual processing may occur such as application of the discrete cosine transform ( dct ) or other transforms , quantization , entropy encoding ( e . g ., huffman encoding , arithmetic encoding , etc . ), association of motion vectors , and / or the like . the typical processing defined by the mpeg standards may be employed . after compression , the data can be recovered using traditional processing . for example , conventional mpeg decoders may be used to recover the compressed data . due to the application of the transform function ( s ), the exact video data of a particular frame might not be recovered ( i . e ., the compression is lossy ). however , the transform functions are preferably selected such that erroneous or otherwise less important information is omitted from the residual data . accordingly , the viewer of the decompressed video data does not experience an undue reduction in the image quality . although fig1 describes compression of video data , the present invention is not so limited . some representative embodiments may be employed upon any type of data that is amenable to lossy compression . fig2 depicts function 200 that may be applied to residual data according to one representative embodiment . function 200 is a piece - wise linear function of the sad value . function 200 is divided into several regions with each region having its own parameter value ( in the simplified linear case , the slope of the line ). for small sad values , the line can be steep so that the optimal residual data is reduced ( to reflect the fact that the difference may be noise or an error ). alternatively , for larger sad values , the line becomes flat so that the full residual value can be encoded . the regions can be obtained via training or previous statistics . fig3 and 4 depict functions 300 and 400 respectively according to other representative embodiments . function 300 suppresses differences associated with small sad values while emphasizing differences associated with larger sad values ( e . g ., “ important ” new video features ). function 400 possesses a “ bandpass ” shape . differences associated with small and large sad values are suppressed . function 400 may be applied when prior knowledge indicates that large difference values may be unreliable and , hence , should be suppressed . in other embodiments , the transform functions may similarly be functions of energy , entropy , and / or motion vectors . fig5 depicts system 500 that compresses video data according to one representative embodiment . system 500 may be implemented using a computer platform that includes suitable computing resources such as processor 501 , display 502 , and non - volatile memory 503 . non - volatile memory 503 may be used to store code or software instructions that perform the compression of video data 504 . for example , a current video frame may be processed by best - matching block module 505 . after the identification of best matching blocks for a current frame of data from one or several reference frames , conventional residual calculation module 506 generates a residual frame . transform function ( s ) module 507 uses one or several variables to scale the data values of the conventional residual frame to generate an optimal residual frame . the variables may include sad values , energy values , motion vector values , and / or the like . transform function module ( s ) 507 removes information from the residual frame that is not important to image quality or that may represent noise or errors . the optimal residual frame is processed by mpeg encoding module 508 to generate compressed video data 509 . compressed video data 509 can be accessed using conventional mpeg decoder / viewer module 510 . although mpeg encoding has been discussed for some representative embodiments , any suitable encoding scheme may be employed according to other representative embodiments . additionally , although some representative embodiments may been described in terms of software , other suitable logic elements could be employed such as integrated circuitry . although the present invention and its advantages have been described in detail , it should be understood that various changes , substitutions and alterations can be made herein without departing from the invention as defined by the appended claims . moreover , the scope of the present application is not intended to be limited to the particular embodiments of the process , machine , manufacture , composition of matter , means , methods and steps described in the specification . as one will readily appreciate from the disclosure , processes , machines , manufacture , compositions of matter , means , methods , or steps , presently existing or later to be developed that perform substantially the same function or achieve substantially the same result as the corresponding embodiments described herein may be utilized . accordingly , the appended claims are intended to include within their scope such processes , machines , manufacture , compositions of matter , means , methods , or steps .