Systems and methods for block recomposition for compound image compression
View Patent ↗A new approach is proposed that contemplates systems and methods to support block-based compression of a compound image by skipping “don't care” blocks in the layers of the image while neither introducing significant overhead nor requiring changes to the compression method used. The block-based compression approach first segments a compound image into multiple layers and then recomposes a new set of image layers, possibly with new dimensions, from only the non-“don't care” blocks in the layers of the original image. The approach may later decompress the compressed image layers and restore the image by copying the decompressed blocks to their respective positions in the original image.
1. A system, comprising:
an image segmentation engine running on a host, which in operation, decomposes a compound image into one or more original image layers;
a layer recomposition engine running on the host, which in operation,
identifies “don't care” blocks in each of the one or more original image layers;
recomposes the one or more original image layers into one or more corresponding new image layers having new dimensions by skipping the “don't care” blocks in the one or more original image layers, wherein no value is assigned to each of the skipped “don't care” blocks in the one or more original image layers;
a layer compression engine running on the host, which in operation, processes and compresses each of the one or more new image layers, wherein each of the one or more new image layers has an associated compressor, the associated compressor being selected based on a content of the new image layer.
2. The system of claim 1 , further comprising:
an image decompression and composition engine running on the host, which in operation,
retrieves, decompresses, and processes each of the compressed one or more layers;
reconstructs the original image from the decompressed one or more layers.
3. The system of claim 2 , wherein the image decompression and composition engine reconstructs the original image based on the MRC imaging model used.
4. The system of claim 2 , wherein the image decompression and composition engine reconstructs the original image by copying every block in the one or more new image layers to its original position in the original image.
5. The system of claim 1 , wherein the host is a computing device, a communication device, s storage device, or any electronic device capable of running a software component.
6. The system of claim 1 , wherein the image segmentation engine decomposes the compound image based on Mixed Raster Content (MRC) imaging model.
7. The system of claim 6 , wherein the MRC imaging model comprises a foreground layer, a background layer, and a mask layer.
8. The system of claim 7 , wherein the mask layer is implicitly coded by a transparent color in the foreground layer.
9. The system of claim 6 , wherein the MRC imaging model comprises one background layer and one or more pairs of foreground and mask layers.
10. The system of claim 1 , wherein the image segmentation engine decomposes and represents the compound image as one, two, three, or more layers, depending on the content of the image.
11. The system of claim 1 , wherein the layer recomposition engine selects possible new dimensions for each of the one or more new image layers that hold all non-“don't care” blocks in the corresponding original image layers.
12. The system of claim 1 , wherein the layer recomposition engine recomposes each of the one or more new image layers by copying all non-“don't care” blocks in each of the one or more original image layers into the corresponding new image layer.
13. The system of claim 1 , wherein the layer recomposition engine eliminates or reduces overhead introduced by “don't care” blocks in the one or more original image layers.
14. The system of claim 1 , wherein the compressor is one of JPEG, MMR, JBIG, PWC, and PNG.
15. The system of claim 1 , wherein the compressor adopts an associated compression approach and compression parameters.
16. The system of claim 1 , wherein the layer compression engine chooses the compressor for each of the new image layer based on type of content of the layer.
17. The system of claim 1 , wherein the layer compression engine packages the compressed one or more layers in a format suitable for delivery.
18. A computer-implemented method, comprising:
segmenting, at one or more processors, a compound image into one or more original image layers;
identifying, at the one or more processors, “don't care” blocks in each of the one or more original image layers;
recomposing, at the one or more processors, the one or more original image layers into one or more corresponding new image layers having new dimensions by skipping the “don't care” blocks in the one or more original image layers, wherein no value is assigned to each of the skipped “don't care” blocks in the one or more original image layers;
processing and compressing, at the one or more processors, each of the one or more recomposed image layers, wherein each of the one or more new image layers has an associated compressor, the associated compressor being selected based on a content of the new image layer.
19. The method of claim 18 , further comprising: retrieving, decompressing, and processing each of the compressed one or more layers; reconstructing the original image from the decompressed one or more layers.
20. The method of claim 19 , further comprising: reconstructing the original image based on the MRC imaging model used.
21. The method of claim 19 , further comprising: reconstructing the original image by copying every block in the one or more new image layers to its original position in the original image.
22. The method of claim 18 , further comprising: decomposing the compound image based on Mixed Raster Content (MRC) imaging model.
23. The method of claim 18 , further comprising: decomposing and representing the compound image as one, two, three, or more layers, depending on the content of the image.
24. The method of claim 18 , further comprising: selecting possible new dimensions for each of the one or more new image layers that hold all non-“don't care” blocks in the corresponding original image layers.
25. The method of claim 18 , further comprising: recomposing each of the one or more new image layers by copying all non-“don't care” blocks in each of the one or more original image layers into the corresponding new image layer.
26. The method of claim 18 , further comprising: eliminating or reducing overhead introduced by “don't care” blocks in the one or more original image layers.
27. The method of claim 18 , further comprising: choosing the compressor for each of the new image layer based on type of content of the layer.
28. The method of claim 18 , further comprising: packaging the compressed one or more layers in a format suitable for delivery.
29. The method of claim 18 , further comprising: choosing the compressor for each of the new image layer based on type of content of the layer.
30. A non-transitory computer-readable storage medium having executable software instructions stored thereon that when executed causes a system to:
segment a compound image into one or more original image layers;
identify “don't care” blocks in each of the one or more original image layers;
recompose the one or more original image layers into one or more corresponding new image layers having new dimensions by skipping the “don't care” blocks in the one or more original image layers, wherein no value is assigned to each of the skipped “don't care” blocks in the one or more original image layers;
compress each of the one or more recomposed image layers, wherein each of the one or more new image layers has an associated compressor, the associated compressor being selected based on a content of the associated new image layer;
retrieve, decompress, and process each of the compressed one or more layers; and
reconstruct the original image from the decompressed one or more layers.