Method, system and computer program product for providing entropy constrained color splitting for palette images with color-wise splitting
AssigneeSlipstream Data Inc.
InventorsEn-hui Yang, Longji Wang
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AssigneeSlipstream Data Inc.
InventorsEn-hui Yang, Longji Wang
Estimating the term…
A method, system and computer program product for progressively encoding a digitized color image is provided. This involves: initializing a tree structure with at least one starting leaf node; determining at least one representative color for each starting leaf node; and growing the tree structure and updating an encoded image by repeatedly (i) selecting a leaf node n to become a non-leaf node n linked to two new leaf nodes based on an associated achievable cost; (ii) creating the two new leaf nodes by re-allocating each color in n; (iii) determining a representative color for each of the two new leaf nodes; and (iv) encoding the index information associated with the selected leaf node n, the representative colors of the two new leaf nodes, and information regarding a plurality of pixels of the digitized color image corresponding to the two representative colors of the two new leaf nodes.
A method for progressively encoding a digitized color image with M distinct colors allocated to a set of pixels using a data processing system, the digitized color image being provided by assigning each of the M distinct colors to an associated subset of pixels in the set of pixels, the method comprising:
A computer program product for use on a computer system comprising a non-transitory computer-readable medium comprising instructions that, when executed by a processor of the computer system, cause the processor to perform acts of a method to progressively encode a digitized color image with M distinct colors allocated to a set of pixels, the digitized color image being provided by assigning each of the M distinct colors to an associated subset of pixels in the set of pixels, the acts comprising:
A system for progressively encoding a digitized color image with M distinct colors allocated to a set of pixels, the digitized color image being provided by assigning each of the M distinct colors to an associated subset of pixels in the set of pixels, the system comprising a processor and a memory, the processor configured to:
Dependencies are inferred from the claim text.
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Colour picture communication systems: systems for the transmission or the storage of the colour picture signal; Details therefor, e.g. coding or…
Characterised by the element, parameter or selection affected or controlled by the adaptive coding: selection of coding mode or of prediction mode
Data rate or code amount at the encoder output: according to rate distortion criteria
Characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the…: the…
Term ended 25 Sep 2026 (estimated)
Pictures with thousands or millions colors can be represented as true color images, storing the exact color for each pixel in the formats such as BMP (bitmap) and JPEG. In contrast, pictures containing only a few (typically up to 256) colors can be stored more efficiently as colormapped images or palettized images like the well known GIF (Graphics Interchange Format) or PNG (Portable Network Graphics) format. A significant portion of web images are in the format of GIF or PNG.
When browsing palettized images over low-bandwidth communication links, such as wireless links or dial-up links, progressive transmission of these palette images can support fast browsing since it enables the users to view complete versions of these images (but at a low resolution) before all progressively coded image data has been received. However, even though both GIF and PNG support an interlaced format, which refines the resolution of an image progressively by encoding the image in multiple passes and skipping a number of pixels in each pass, interlaced GIF and PNG are not in a progressive format in the strict sense that the color information of each pixel is refined progressively up to lossless recovery.
Rauschenbach investigated the progressive refinement of color information for palette images in his so-called MCQ (Mobile visualization Color Quantized format) method (U. Rauschenbach, “Compression of palettized images with progressive coding of the color information,” in Proc. SPIE Visual
For a better understanding of the various embodiments described herein and to show more clearly how they may be carried into effect, reference will now be made, by way of example only, to the accompanying drawings which show at least one exemplary embodiment and in which:
FIG. 1 in a flow chart, illustrates an overall algorithm for entropy constrained color splitting for palette images with color wise splitting between leaf nodes in accordance with an aspect of an embodiment of the invention;
FIG. 2 in a flow chart, illustrates an overall algorithm for entropy constrained color splitting for palette images with pixel wise splitting between leaf nodes in accordance with a further aspect of a further embodiment of the invention;
Pictures with thousands or millions colors can be represented as true color images, storing the exact color for each pixel in the formats such as BMP (bitmap) and JPEG. In contrast, pictures containing only a few (typically up to 256) colors can be stored more efficiently as colormapped images or palettized images like the well known GIF (Graphics Interchange Format) or PNG (Portable Network Graphics) format. A significant portion of web images are in the format of GIF or PNG.
When browsing palettized images over low-bandwidth communication links, such as wireless links or dial-up links, progressive transmission of these palette images can support fast browsing since it enables the users to view complete versions of these images (but at a low resolution) before all progressively coded image data has been received. However, even though both GIF and PNG support an interlaced format, which refines the resolution of an image progressively by encoding the image in multiple passes and skipping a number of pixels in each pass, interlaced GIF and PNG are not in a progressive format in the strict sense that the color information of each pixel is refined progressively up to lossless recovery.
Rauschenbach investigated the progressive refinement of color information for palette images in his so-called MCQ (Mobile visualization Color Quantized format) method (U. Rauschenbach, “Compression of palettized images with progressive coding of the color information,” in Proc. SPIE Visual Communications and Image Processing (VCIP2000), Perth, Australia, June 2000, hereinafter referred to as [1]). Unlike the interlaced GIF and PNG formats, the refinement of color information in MCQ is done bit-plane by bit-plane, and allows the early recognition of shapes with fine details (e.g. text), normally after decoding a small portion of the compressed bit stream. Although MCQ supports progressive refinement of color information in contrast to resolution refinement, it only achieves a compression ratio comparable to GIF or PNG format. To improve the compression ratio while supporting the progressive transmission of palette images, Chen et al. (X. Chen, S. Kwong, and J. Feng, “A new compression scheme for color-quantized images,” IEEE Transactions on Circuits and System for Video Technology, Vol. 12, No. 10, pp. 904˜908, October 2002, hereinafter referred to as [2]) proposed a new color refinement scheme based on MCQ and the distortion-based hierarchical splitting color quantization algorithm pioneered by Orchard and Bouman (M. Orchard and C. Bouman, “Color quantization of images,” IEEE Transactions on Signal Processing, Vol. 39, No. 12, pp. 2677˜2690, December 1991, hereinafter referred to as [3]). Unlike MCQ where the color information is refined bit-plane by bit-plane with the number of bit-planes equal to the color depth of the palette, Chen's algorithm refines the color information color by color. For lossless compression of palette images, the color splitting algorithm proposed in [2] achieves around 30˜40% size reduction compared to GIF or PNG format in addition to its decent feature of supporting the progressive transmission.