Image denoising with multiple layer block matching and 3D filtering

Zhigang Fan

doi:10.1117/12.2045599

3 March 2014 Image denoising with multiple layer block matching and 3D filtering

Zhigang Fan

Proceedings Volume 9027, Imaging and Multimedia Analytics in a Web and Mobile World 2014; 90270H (2014) https://doi.org/10.1117/12.2045599
Event: IS&T/SPIE Electronic Imaging, 2014, San Francisco, California, United States

Abstract

Block Matching and 3-D Filtering (BM3D) algorithm is currently considered as one of the most successful denoising algorithms. Despite its excellent results, BM3D still has room for improvements. Image details and sharp edges, such as text in document images are challenging, as they usually do not produce sparse representations under the linear transformations. Various artifacts such as ringing and blurring can be introduced as a result. This paper proposes a Multiple Layer BM3D (MLBM3D) denoising algorithm. The basic idea is to decompose image patches that contain high contrast details into multiple layers, and each layer is then collaboratively filtered separately. The algorithm contains a Basic Estimation step and a Final Estimation step. The first (Basic Estimation) step is identical to the one in BM3D. In the second (Final Estimation) step, image groups are determined to be single-layer or multilayer. A single-layer group is filtered in a same manner as in BM3D. For a multi-layer group, each image patch within the group is decomposed with the three-layer model. All the top layers in the group are stacked and collaboratively filtered. So are the bottom layers. The filtered top and bottom layers are re-assembled to form the estimation of the blocks. The final estimation of the image is obtained by aggregating estimations of all blocks, including both single-layer and multi-layer ones. The proposed algorithm shows excellent results, particularly for the images containing high contrast edges.

Citation Download Citation

Zhigang Fan "Image denoising with multiple layer block matching and 3D filtering", Proc. SPIE 9027, Imaging and Multimedia Analytics in a Web and Mobile World 2014, 90270H (3 March 2014); https://doi.org/10.1117/12.2045599

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