GENERAL BANDING AND CODEC BANDING ARTIFACT REMOVAL

• US 20130128122A1
• Filed: 11/23/2011
• Published: 05/23/2013
• Est. Priority Date: 11/23/2011
• Status: Active Grant

• Current Assignee: STMicroelectronics Asia Pacific Pte Limited (STMicroelectronics NV)
• Original Assignee: STMicroelectronics Asia Pacific Pte Limited (STMicroelectronics NV)
• Inventors: HUI, Lucas, WANG, Haiyun
• Granted Patent: US 8,731,323 B2
• Time in Patent Office: Days
• US Class Current: 348/607
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/10024 Color image
• CPC Class Codes: G06T 2207/20012 Locally adaptive
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: H04N 19/86 involving reduction of coding artifacts, e.g. of blockiness
• CPC Class Codes: H04N 5/142 Edging; Contouring
• CPC Class Codes: H04N 5/21 Circuitry for suppressing or minimising disturbance, e.g. moiré or halo

Abstract

A method and apparatus are disclosed for identifying and removing banding artifacts (i.e., false contours) resulting from insufficient bit depth caused by digital image quantization, conversion, and/or compression. This method includes: explicitly identifying texture block and flat block; de-termination of filter window sizes with the consideration of handling transitions between texture block and flat block; de-banding filtering with edge protection; and noise shaping according to de-banding filter result.

Claims

1. An apparatus for removing banding artifacts, comprising:

a block classification processing module; and

a de-banding filtering module coupled to the block classification processing module.

2. The apparatus of claim 1, further comprising a noise shaping processing module coupled to the de-banding filtering module.

3. The apparatus of claim 1, wherein the block classification processing module is configured to perform coded block location based image feature extraction and block type identification.

4. The apparatus of claim 1, wherein the de-banding filtering module is configured to be applied to each pixel according to a filtering window.

5. The apparatus of claim 4, wherein the de-banding filtering module is further configured to be steered by a definable sigma.

6. The apparatus of claim 2, wherein the noise shaping processing module is configured to be conducted according to filtering results of the de-banding filtering module.

7. The apparatus of claim 1, wherein the block classification processing module comprises:

an edge detection unit; and

a block classification unit coupled to the edge detection unit.

8. The apparatus of claim 7, wherein the edge detection unit is configured to extract block-wise features of a coded block.

9. The apparatus of claim 7, wherein the block classification unit is configured to differentiate flat blocks and texture blocks.

10. The apparatus of claim 1, wherein the de-banding filtering module comprises:

a window size assignment unit; and

a de-banding filtering unit coupled to the window size assignment unit.

11. The apparatus of claim 9, wherein the window size assignment unit is configured to determine a filtering window for a pixel.

12. The apparatus of claim 10, wherein the filtering window is adaptively determined according to distance to boundary of flat block and texture block.

13. The apparatus of claim 9, wherein the de-banding filtering unit is configured to removing banding artifacts according to the equation

14. The apparatus of claim 2, wherein the noise shaping processing module is configured to calculate a gray value difference between a de-banding output data and an original input frame, multiply the gray value difference with a spatial/temporal noise generated by a noise shaping unit as an adding-back-randomness, and adding the adding-back randomness to the de-banding output.

15. The apparatus of claim 14, wherein the noise shaping unit is configured to generate temporal, spatial and pure flat noise.

16. A method for block classification comprising calculating a block max edge magnitude and a normalized block min edge magnitude as two axes of a 2D mask, wherein a value of the block max edge magnitude and the normalized block min edge magnitude represents the probability of banding artifacts.

17. The method of claim 16, further comprising applying thresholdings to determine flat blocks and texture blocks.

18. A method for noise generation and noise shaping, comprising, if temporal noise is enabled, updating a seed of a noise generator temporally on each frame, otherwise, applying a fixed seed over a whole sequence.

19. The method of claim 18, further comprising if spatial noise is enabled, adaptively adding a spatial noise on each pixel if a de-banding filter-in-out difference is not equal to zero.

20. The method of claim 19, wherein noise strength control on luma/chroma is applied to the adaptively adding of the spatial noise.

21. The method of claim 19, further comprising if pure flat noise is enabled, the spatial noise can be added on pure flat pixels.

22. The method of claim 21, wherein pure flat pixels are detected by checking whether the de-banding filter-in-out difference equals to zero.

23. A method for removing banding artifacts, comprising:

conducing block classification based on coded block location and block max/min edge analysis to explicitly identify texture block and flat block;

determining a de-banding window size according to surrounding block classifications and current pixel position within a current block to handle transitions between texture block and flat block;

applying a de-banding filter to the current pixel according to determined the de-banding window size; and

applying a noise shaping function according to a result of the de-banding filter to fine tune transitions between mono-tone region, de-banding region, and re-quantized output result.

24. The method of claim 23, wherein applying the de-banding filter is further steered by a definable sigma to improve filtering on banding region and protect texture edge features.