Self-Adaptive Image Processing Using Blind Image Quality Assessment Technique

Publication date: Available online 5 July 2016 Source:Perspectives in Science Author(s): K.S. Prasada Kumari Image processing techniques for filtering noise is a major challenge for DSP Engineers. When the images are corrupted by noise whose characteristics cannot be evaluated apriori, processing systems need to be flexible and adaptable. General purpose filters based on assumptions about image noise models fail to meet the quality and performance criteria in dealing with unmodeled noise. At the same time, evolutionary algorithms based adaptable filter architecture is proved to be successful in this regard. While existing evolutionary techniques based designs use uncorrupted reference image and compute mean absolute error for evolving a noise filter, the paper proposes a novel noise quality index based technique. The proposed entropy based scheme estimates noise content without any reference image and such a system is vital in situations where uncorrupted image reference is unavailable. Based on experimental results, the paper compares no-reference image noise assessment techniques with reference based technique and concludes that the proposed blind noise assessment method is accurate as referenced based techniques. From implementation point of view, the no-reference scheme is computationally intensive.

Source: Perspectives in Science - July 14, 2016 Category: Science Source Type: research