Pyramidal Decomposition for Multi-Resolution Image Filtering

• US 20080152251A1
• Filed: 01/27/2006
• Published: 06/26/2008
• Est. Priority Date: 01/31/2005
• Status: Abandoned Application

• Current Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: Picard, Mathieu, Samson, Christophe, Florent, Raoul
• Application Number:
  US11/814,817
• Publication Number:
  US 20080152251A1
• Time in Patent Office: Days
• US Class Current: 382/260
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/73 Deblurring; Sharpening

Abstract

A modified Laplacian-pyramid method and system filters (340-360, 440-460) the Gaussian image at each level (31-33, 41-43) of the pyramid, and uses the filtered Gaussian image (341-361, 441-461) to produce the Laplacian-pyramid images (349-369, 449-469). The filtering of the Gaussian image is adaptive, and based at least in part on the characteristics of the Gaussian image at each stage. In one example embodiment, two filters (F1, F2) are used at each stage, and the Laplacian image (349-369) is based on a filtered version of the Gaussian image and an upsampled filtered version of a downsampling (346-366) of the Gaussian image. In another example, filter is used, and the Laplacian image (449-469) is based on the filtered version (441-461) of the Gaussian image and an upsampled downsampling (446-466) of the filtered version of the Gaussian image. By forming the Laplacian images (349-369, 449-469) from the filtered Gaussian images (341-361, 441-461), the aliasing conventionally produced by filtering the Laplacian images is substantially reduced.

Claims

1. An image processing system comprising:

a plurality of stages (31-33, 41-43), each stage of the plurality of stages (31-33, 41-43) including;

a downsampler (110, 120, 130) that is configured to receive an input image (101, 111, 129) and to produce therefrom a first downsampled image (111, 121, 131) that is provided as the input image of a subsequent stage (32-33, 42-43),

a filter (340-360, 440-460) that is configured to filter the input image (101, 111, 129) and to produce therefrom a filtered image (341-361, 441-461),

an upsampler (115, 125, 135) that is configured to receive a second downsampled image (346-366, 446-466) and to provide therefrom an upsampled image (116, 126, 136), and

a subtractor (140, 150, 160) that is configured to subtract the upsampled image (116, 126, 136) from the filtered image (341-361, 441-461), to provide therefrom a Laplacian image (349-369, 449-469) based on the filtered image (341-361, 441-461).

2. The image processing system of claim 1, wherein

each stage further includes

a second filter (345-365) that is configured to filter the first downsampled image (111-131) and to produce therefrom the second downsampled image (346-366, 446-466).

3. The image processing system of claim 1, wherein

each stage further includes

a second downsampler (445-465) that is configured to receive the filtered image (441-461) and to produce therefrom the second downsampled image (446-466).

4. The image processing system of claim 1, wherein

each stage further includes

an adaptation component (310-330, 410-430) that is configured to determine coefficients for use by the filter (340-360, 440-460), based on the input image (101, 111, 129).

5. The image processing system of claim 1, wherein

the filter (340-360, 440-460) is further configured to filter the input image (101, 111, 129) based on one or more characteristics of the first downsampled image (111, 121, 131).

6. The image processing system of claim 1, wherein

the filter (340-360, 440-460) at at least one stage of the plurality of stages (31-33, 41-43) is further configured to filter the input image (101, 111, 129) based on one or more characteristics of one or more of the input images (111, 129) at subsequent stages (32-33, 42-43) of the plurality of stages (31-33, 41-43).

7. The image processing system of claim 1, further including

a re-composer that is configured to receive images corresponding to the Laplacian image (349-369, 449-469) from each of the stages (31-33, 41-43), and the first downsampled image of a last stage (33, 43) of the plurality of stages (31-33, 41-43), and to produce therefrom an output image (171, 181, 191).

8. A method of processing an image, comprising:

downsampling (110) an input image (101) to produce a first downsampled image (111) at a first stage (31, 41) of a plurality of stages (31-33, 41-43) that forms an input image (111) to a second stage (32, 42) of the plurality of stages (31-33, 41-43);

filtering (340, 440) the input image (101) to produce a filtered image (341, 441);

upsampling (115) a second downsampled image (346, 446) to provide an upsampled image (116); and

subtracting (140) the upsampled image (116) from the filtered image (341, 441) to produce a Laplacian image (349, 449) based on the filtered image (341, 441).

9. The method of claim 8, further including:

downsampling (120) the input image (111) of the second stage (32, 42) to produce a first downsampled image (121) at the second stage (32, 42) that forms an input image (121) to a third stage of the plurality of stages (31-33, 41-43);

filtering (350, 450) the input image (111) of the second stage (32, 42) to produce a filtered image (342, 442) at the second stage (32, 42);

upsampling (125) a second downsampled image (356, 456) at the second stage (32, 42) to provide an upsampled image (126) at the second stage (32, 42); and

subtracting (150) the upsampled image (126) at the second stage (32, 42) from the filtered image (342, 442) at the second stage (32, 42) to produce a Laplacian image (359, 459) based on the filtered image (342, 442) at the second stage (32, 42).

10. The method of claim 9, further including:

repeating the downsampling (130), filtering (360), upsampling (135), and subtracting (160) at the third and subsequent stages (33, 43) of the plurality of stages (31-33, 41-43).

11. The method of claim 8, further including

filtering (345, 355, 365) the first downsampled image (111, 121, 131) at each stage of the plurality of stages (31-33) to produce the second downsampled image (346-366) at each stage.

12. The method of claim 8, further including

downsampling (445-465) the filtered image (441-461) at each stage of the plurality of stages (41-43) to produce the second downsampled image (446-466) at each stage.

13. The method of claim 8, further including

determining (310-330, 410-430) coefficients the filtering at each stage of the plurality of stages (31-33, 41-43), based on the input image (101, 111, 129) at each stage.

14. The method of claim 13, further including

determining additional coefficients for the filtering (440-460) at each stage, based on the first downsampled image (111 -131) at each stage.

15. The method of claim 13, further including

determining additional coefficients for the filtering (440-460) at at least one stage (31, 41), based on one or more of the input images (111, 129) at one or more of the other stages (32-33, 42-43) of the plurality of stages (31-33, 41-43).

16. The method of claim 8, further including

recomposing an output image (141, 181, 191), based on images corresponding to the Laplacian image (349-369, 449-469) at one or more stage, and the first downsampled image (131) of a last stage (33, 43) of the plurality of stages (31-33, 41-43).