Image Reconstruction and Refinement

Abstract

Image reconstruction has been expanded dramatically over the last few years. As the field of image processing increases vastly in different fields for different uses. The use of different techniques in it also increases like; image compression, image enhancement, image segmentation, image manipulation, image generation and image reconstruction for using the same image data for different purposes. The implementation of image processing by different techniques makes it more and more effective and easy to use with proper knowledge. Image reconstruction is one of the image processing techniques used to regain or recreate any image. Image reconstruction is done for image processing to reconstruct images that contain noise or any other factor that degrades an image. There are different types of noises like: gaussian noise, poisson noise, s&p noise, speckle noise etc. This image noise can be caused by various physical and environmental effects. The image reconstruction techniques mainly regain the features of the image that are lost by any factor that affects an image. In this paper, we used wavelet transform denoising techniques and denoising filters to reconstruct the images for eliminating noise.