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A Performance comparison of single Image reconstruction techniques under several Noisy environments



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Due to Noise contamination on the image during the observation process, Digital Image reconstruction is an essential in terms of recovering the information of the contents (e.g. document and image) and utilized in many applications such as digital image forensic, Medical Image processing, machine vision, and etc. Therefore, this paper is concerned with the Performance comparisons of single image employing various reconstruction approaches. These are Inverse filter, Wiener filter, Regularized technique, Lucy-Richardson technique, and Bayesian technique based on median, mean, myriad, and meridian filters. The experiments test on the three standard pictures (Lena, Resolution chart, and Susie (40th)) under the same Noise conditions. Four types of Noise models consider in this paper are AWGN, Poisson, Salt-Pepper, and Speckle noises. The performance of evaluations is done by Varying parameters of individual technique. Peak-signal-to-noise-ratio (PSNR) is a Key indicator on the Performance comparison results. © 2011 IEEE.

Digital image reconstruction (10 items found) | Medical Image Processing (42 items found) | Performance comparison (65 items found) | Image reconstruction (192 items found) | Noise contamination (2 items found) | Varying parameters (10 items found) | Image processing (1014 items found) | Noise conditions (4 items found) | Key indicator (5 items found) | Speckle noise (32 items found) | Noise models (15 items found) | Digital image reconstructionBayesian techniques | Single-image reconstruction | Peak signal to noise ratio | Digital image enhancement | Digital image processing | Digital image forensics | Noisy environment | Computer vision | Medical imaging | Inverse filters | Computer crime | WIENER filters | Single images | Internet |

ต้นฉบับข้อมูล : scopus