Performance evaluation for 2D and 3D filtering methods of noise removal in color images

摘要

Color images formed by modern digital cameras are often noisy, especially if they are captured in bad illumination conditions. This makes desirable to remove the noise by image pre-filtering. A specific feature of the noise observed for the considered application is that it can be spatially correlated. Filters to be applied have to effectively suppress noise introducing only negligible distortions into processed images. Moreover, such filters have to be fast enough and tested for a variety of natural images and noise properties. Another specific requirement is that a visual quality of processed images has to be paid a specific attention. To carry out intensive testing of some denoising approaches, a recently designed database TID2008 of distorted images provides a good opportunity since it contains 25 different images corrupted by i.i.d. and spatially correlated noise with several levels of variances. Taking into account the known fact that the color components are highly correlated, both modern 2D (component-wise) and 3D (vector) filtering techniques are studied. It is demonstrated that the use of 3D filters that allow exploiting inter-channel correlation provides considerably better results in terms of conventional and visual quality metrics. It is also shown how 3D filter based on discrete cosine transform (DCT) can be adapted to a spatial correlation of noise. This adaptation produces sufficient increase of the filter's efficiency. Examples of filter's performance are presented.