Texture compression techniques

US9418450B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9418450-B2
Application numberUS-51319006-A
CountryUS
Kind codeB2
Filing dateAug 31, 2006
Priority dateAug 31, 2006
Publication dateAug 16, 2016
Grant dateAug 16, 2016

How to read this patent

A practical reading order for non-experts. Skip the full description unless you need deep technical detail.

  1. Title

    What the patent document calls the invention.

  2. Abstract

    A short plain-language summary of the technical disclosure.

  3. Assignees and inventors

    Who owns or filed the patent and who is credited as inventor.

  4. Key dates

    Filing, priority, publication, and grant dates set the timeline.

  5. First independent claim

    The legal scope of protection — read this for what is actually claimed.

  6. CPC / IPC classifications

    Technology tags used to group this patent with similar filings.

  7. Citations and related patents

    Prior art links and similar publications in this corpus.

Abstract

Official abstract text for this publication.

A texture compression method is described. The method comprises splitting an original texture having a plurality of pixels into original blocks of pixels. Then, for each of the original blocks of pixels, a partition is identified that has one or more disjoint subsets of pixels whose union is the original block of pixels. The original block of pixels is further subdivided into one or more subsets according to the identified partition. Finally, each subset is independently compressed to form a compressed texture block.

First claim

Opening claim text (preview).

What is claimed is: 1. A texture compression method, comprising: (a) splitting an original texture having a plurality of pixels into original blocks of pixels; for each of the original blocks of pixels: (b) identifying a partition from a predefined set of partitions, the partitions having one or more disjoint and variably shaped subsets of pixels whose union is the original block of pixels; (c) subdividing the original block of pixels into one or more subsets according to the identified partition; (d) independently compressing each subset to form a compressed texture block; and (e) decompressing the compressed texture block to obtain an approximation of the original block of pixels; (f) comparing the original block of pixels to the approximation of the original block of pixels to obtain a quality parameter for the identified partition; (g) repeating steps (b) through (f) for each partition in the predefined set of partitions to obtain the quality parameter for each partition; (h) choosing a final partition for the original block of pixels that yields an optimal quality parameter; (i) subdividing the original block of pixels into one or more final subsets according to the final partition; and (j) independently compressing each final subset to form a compressed texture block. 2. The method of claim 1 , further comprising: for each original block of pixels, evaluating a function for the original block of pixels; identifying a partition based on the evaluated function; and repeating (c) and (d). 3. The method of claim 1 , wherein the final partition is selected for the original block of pixels if the quality parameter for the identified partition meets a pre-selected threshold and the final partition is selected that either meets the pre-selected threshold or is closest to the pre-selected threshold when none of the partitions meet the pre-selected threshold. 4. The method of claim 1 , wherein (b) further comprises identifying the partition from a predefined set of partitions wherein the subsets have a different number of pixels. 5. The method of claim 1 , wherein the predefined set of partitions includes an explicitly defined base set of partitions and additional sets of partitions derived from the base set. 6. The method of claim 5 , wherein each derived partition is obtained from a partition of the base set by performing unions of some of its subsets. 7. The method of claim 1 , wherein (d) further comprises compressing the pixels in each subset using a lossy compression method. 8. The method of claim 1 , wherein (d) comprises compressing each of the subsets using two explicit endpoint parameters and a number of intermediate points defining a ramp in the color space. 9. The method of claim 1 , wherein (d) comprises compressing each of the subsets using a palletization technique. 10. The method of claim 1 , wherein the quality parameter is based on a root-mean-square error for the block. 11. The method of claim 1 , wherein the quality parameter is based on chrominance error parameter for the block. 12. The method of claim 1 , wherein the quality parameter is based on a luminance parameter for the block. 13. The method of claim 1 , further comprising splitting the texture into regular blocks of 8×8 pixels. 14. The method of claim 1 , further comprising splitting the texture into regular blocks of 4×4 pixels. 15. A computer processing system for texture compression, comprising: a processor configured to (a) split an original texture having a plurality of pixels into original blocks of pixels, wherein for each of the original blocks of pixels, the processor is further configured to: (b) identify a partition from a predefined set of partitions, the partitions having one or more disjoint and variably shaped subsets of pixels whose union is the original block of pixels; (c) subdivide the original block of pixels into one or more subsets according to the identified partition; and (d) independently compress each subset to form a compressed texture block; and (e) decompress the compressed texture block to obtain an approximation of the original block of pixels; (f) compare the original block of pixels to the approximation of the original block of pixels to obtain a quality parameter for the identified partition; (g) repeat steps (b) through (f) for each partition in the predefined set of partitions to obtain the quality parameter for each partition; (h) choose a final partition for the original block of pixels that yields an optimal quality parameter; (i) subdivide the original block of pixels into one or more final subsets according to the final partition; and (j) independently compress each final subset to form a compressed texture block.

Assignees

Inventors

Classifications

  • G06T9/00Primary

    Image coding (bandwidth or redundancy reduction for static pictures H04N1/41; coding or decoding of static colour picture signals H04N1/64; methods or arrangements for coding, decoding, compressing or decompressing digital video signals H04N19/00) · CPC title

  • using feature points or meshes · CPC title

  • Measured or subjectively estimated visual quality after decoding, e.g. measurement of distortion (use of rate-distortion criteria H04N19/147) · CPC title

  • the region being a block, e.g. a macroblock · CPC title

  • Adaptive subdivision aspects, e.g. subdivision of a picture into rectangular or non-rectangular coding blocks · CPC title

Patent family

Related publications grouped by family.

External sources

Frequently asked questions

Answers are generated from the same data shown on this page.

What does patent US9418450B2 cover?
A texture compression method is described. The method comprises splitting an original texture having a plurality of pixels into original blocks of pixels. Then, for each of the original blocks of pixels, a partition is identified that has one or more disjoint subsets of pixels whose union is the original block of pixels. The original block of pixels is further subdivided into one or more subset…
Who is the assignee on this patent?
Iourcha Konstantine, Pomianowski Andrew S C, Ati Technologies Ulc
What technology area does this patent fall under?
Primary CPC classification G06T9/00. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Aug 16 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).