An Efficient Vlsi Architecture of Decision Tree Based Denoising Method for Removal of Impulse Noise in Images

Images are often corrupted by impulse noise in the procedures of image acquisition and transmission. Impulse noise is a category of acoustic noise which includes unwanted sharp sounds like click and pops. To avoid the damage on noise liberated pixels, the switching medium filters are used which consists of impulse detection and noise filtering. In our project, we propose an efficient denoising scheme and its VLSI architecture for the removal of randomvalued impulse noise. To attain the objective of low down cost, a low-complexity VLSI planning is proposed. We employ a decisiontree-based impulse noise detector to detect the strident pixels, and an edge-preserving filter to reconstruct the intensity values of noisy pixels. Furthermore, an adaptive machinery is used to enhance the effects of removal of impulse noise. In our project the decision tree based denoising method (DTBDM) is composed of three modules (isolationmodule), Fringe module, and resemblance module). The isolation module is used to decide whether the pixel value is in a smooth region. The fringe module is used to confirm the result of the isolation module. If isolation module and fringe .module cannot determine whether current pixel belongs to noisy free, the similarity component is used to decide the result. Our extensive experimental results demonstrate that the proposed technique can obtain better performances in terms of both quantitative evaluation and visual quality than the previous lower complexity methods.