An image reconstruction technique based on IPSO-DWT under varying crack

Abstract

Abstract

Image Reconstruction is an important fragment in image processing. It is used to reconstruct the image which is corrupted by noise or that has some scratched regions. In order to improve the reconstruction effectiveness of the existing methods a new image reconstruction technique based on DWT and IPSO is proposed in this paper. The proposed technique is composed two main stages (i) training stage (ii) investigation stage. In training phase, initially the input cracked image is reconstructed by the DWT (Discrete wavelet Transform) method by selecting optimal threshold value using well known optimization technique as IPSO (Improved Particle Swarm Optimization). These selected threshold values are stored in the Threshold Database and they are subjugated in the image reconstruction process. In investigation stage, the threshold value is selected based on the crack level of the testing image. The proposed method is implemented in MATLAB with various cracked images. The performance of the IPSO and DWT based image reconstruction technique is checked with existing PSO and average filtering image reconstruction technique in order to prove the efficiency of the proposed method. However, our proposed methodology provides better intuitive and high-quality reconstructed image for the noisy images than the existing method, in terms of peak signal-to-noise ratio (PSNR).