A COMPARISON BETWEEN VARIOUS IMAGE DENOISING TECHNIQUES
Images are often corrupted with noise during acquisition, transmission, and retrieval from storage media. Many dots can be spotted in a Photograph taken with a digital camera under low lighting conditions. A crucial research is how to filter noise caused by the nature, system and processing of transfers and so on. The noise mixed with the useful images or signals and brings the researchers lots of troubles. In many research areas related, such as target detecting and tracking, edge detecting and image registration, image denoising is the first step of process and the effect of it is very important to the following processes. In this paper, we proposed an image denoising method using partial differential equation and bi-dimensional empirical mode decomposition. The bi-dimensional empirical mode decomposition transforms the image into intrinsic mode functions and residue. Different components of the intrinsic mode functions present different frequency of the image. The different with the classic method of partial differential equation denoising is that we use partial differential equation of the intrinsic mode functions to filter noise. Finally, we reconstruct the image with the filtered intrinsic mode functions and residue. The experiments show the reliability of our algorithm.
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