Research On Image Denoising Algorithm For Mobile Phone Camera Based On Wavelet Transform

Image denoising is an old topic in the field of image processing. Its main purpose is to denoise an image on the premise of more original details. The noise is usually added to the image in the process of gathering and transmission of the image. In numerous denoising methods, wavelet threshold denoising is widely used because of its excellent performance. This paper mainly studies wavelet decomposition, the threshold selection, software writing, etc. The main research contents are as follows:(1) In the wavelet denoising, threshold selection is important.This paper studies several classic threshold methods including VisuShrink, SureShrink and BayesShrink. Simulation experiments and real experiments are designed for these three thresholds. Experimental results show that the classic BayesShrink threshold denoising algorithm has good denoising effect for simulation images, which is better than that of VisuShrink threshold and SureShrink threshold.(2) The image is decomposed and denoised using dual-tree complex wavelet transform because it has more directions. The experimental results show that using dual-tree complex wavelet transform to decompose and denoise image can retain more image details. This paper also studies the bivariate statistical model of wavelet coefficient which can correlate wavelet coefficients between adjacent layers because univariate statistical models can't show the connection between the wavelet coefficients. The experimental results show that the peak signal-to-noise ratio and visual effect of the the image are all increased after using bivariate threshold denoising algorithm.(3) We improve the bivariate threshold denoising algorithm based on dual-tree complex wavelet and make it more effective in engineering application. Major improvement methods include down sampling, subband adaptive noise variance, local gray operation. First, denoise the image after down sampling and get the original big picture; Secondly, calculate noise variance for every subband; Finally, detect the image contour using single scaling wavelet transform algorithm then make the pixies that are not contour to gray and do nothing to other pixies. The experimental results show that the algorithm has more practicability for phone camera image after improvement.(4) We write the wavelet denoising software with VS2010 and achieve the bivariate threshold denoising algorithm based on dual-tree complex wavelet using C language. The software can denoise mobile phone camera images and adopts multithreading to improve the performance. Finally we carry on a performance test to the software to verify the denoising effect of the software.