Method of isomorphic singular manifold projection still/video imagery compression

A method of compressing an image, IO said method comprising the steps of:

• dividing said image IO into segments, each segment having a plurality of pixels;
• calculating the dynamic range of the pixels in each segment;
• selecting a best match canonical polynomial for each of said segments;
• finding substitutes for variables in said canonical polynomial to calculate a modeled surface equation F for each of said segments;
• creating a modeled surface IM for each of said segments by substituting the coordinates of each pixel into the modeled surface equation F;
• storing the coefficients for the modeled surface equation F for each of said segments;
• finding connections between adjacent ones of said segments;
• creating an entire modeled image, IM, from each of said segments;
• finding the difference between the image IO and the entire modeled image IM to create a texture image Id;
• applying standard lossy compression to said texture image Id;
• storing the texture image Id;
• combining the entire modeled image IM and the texture image Id to create a combination image, and
• applying lossless compression to said combination image.

A method of compressing an image having manifolds, said method comprising the steps of:

• modeling the image as a photometric projection of at least one manifold in said image;
• mapping said at least one manifold in coordinates (x,y,B) where the coordinate B is luminance at each point (x,y);
• characterizing the mapping with a polynomial, said polynomial having coefficients;
• sending the coefficients of the polynomial as compressed data.

A method of compressing video, said method comprising the steps of:

• taking a frame F0 of the video;
• segmenting the frame F0 into search blocks;
• predicting a subsequent frame;
• determining the error between the frame F0 and said predicted frame;
• comparing said error to a threshold;
• inserting an I frame as the next subsequent frame if said error exceeds said threshold.

A method of compressed video transmission, the method the steps of:

• taking a first frame FO;
• segmenting said frame FO into blocks;
• compressing each said block by representing it with a canonical polynomial having original coefficients;
• predicting a frame P subsequent to said frame FO;
• determining the error between each block in said frame FO and said predicted frame P;
• accumulating the error determined between each block in said frame FO and said predicted frame P;
• comparing said accumulated error to a threshold;
• if said accumulated error exceeds said threshold, inserting an I frame as the next subsequent frame to said frame FO.

A method of compressed video transmission, the method comprising the steps of:

• taking a first frame FO;
• segmenting said frame FO into blocks;
• compressing each said block by representing it with a canonical polynomial having original coefficients;
• predicting a frame P subsequent to said frame F0;
• comparing each block in said frame F0 with said predicted frame P to determine if there is a match;
• if a match is found in said frame P for a block in said frame F0, sending said coefficients of said polynomial for that block to a decoder;
• if a match is not found for a block in said frame F0, generating new coefficients of said polynomial representing said predicted frame P and sending said new coefficients to said decoder;
• reconstructing said frame F0 in said decoder from said original coefficients and said new coefficients sent to said decoder;
• calculating an error between said frame F0 and said predicted frame P based on said comparing each block in said frame FO with said predicted frame P;
• comparing said error to a threshold;
• if said error does not exceed said threshold, sending a B or P frame as the next subsequent frame to said frame FO;
• if said error exceeds said threshold, inserting an I frame as the next subsequent frame to said frame FO.

A method of compressing a video image, said method comprising the steps of:

• taking a frame FO;
• segmenting FO into blocks and defining motion vectors for said blocks to predict a subsequent frame P having corresponding blocks;
• defining errors between said blocks in said frame FO and said corresponding blocks in said frame P;
• accumulating said errors;
• and
• based on said accumulated error, sending an I frame as the next subsequent frame to said frame FO.

A method of automatically recognizing a target in an image, said method comprising the steps of:

• segmenting said image into segments;
• creating a modeled surface for each segment;
• connecting the segments to create an entire modeled image;
• and
• comparing said entire modeled image to a library of known images to determine if there is a match with a known image in said library of images.

A method of analyzing an image for automatic target recognition, said method comprising the steps of:

• separating the image into texture components and sculpture components;
• applying soft ATR to said sculpture components to create a soft ATR sculpture component;
• combining said texture components and said soft ATR sculpture components to form a combined image;
• applying hard ATR to said combined image.