In a random-valued impulse noise corrupted image, in order to remove impulse noise and, meanwhile, efficiently preserve image edges and details, a novel two-phase detail- preserving random-valued impulse noise removal...In a random-valued impulse noise corrupted image, in order to remove impulse noise and, meanwhile, efficiently preserve image edges and details, a novel two-phase detail- preserving random-valued impulse noise removal algorithm is proposed. At the noise detecting phase, an image statistic called S-estimate based rank-ordered absolute difference （S- ROAD） is presented to distinguish image edge and detail pixels from impulse noise pixels in a noise corrupted image. By introducing S-estimate into ROAD statistic, the interference caused by the image edges and details in the ROAD statistic is eliminated. With the S-ROAD statistic, most of the noise pixels, including the noise at edges and details, can be distinguished. At the noise pixels filtering phase, a two-threshold iterative method is used to restore the identified noise pixels and the estimate precision is improved; thus, the image details can be efficiently preserved. Experimental results show that the proposed method provides a significant improvement over many existing filters in terms of both subjective and objective evaluations.展开更多
基金The National Key Technologies R&D Program of China during the12th Five-Year Period(No.2012BAJ23B02)
文摘In a random-valued impulse noise corrupted image, in order to remove impulse noise and, meanwhile, efficiently preserve image edges and details, a novel two-phase detail- preserving random-valued impulse noise removal algorithm is proposed. At the noise detecting phase, an image statistic called S-estimate based rank-ordered absolute difference （S- ROAD） is presented to distinguish image edge and detail pixels from impulse noise pixels in a noise corrupted image. By introducing S-estimate into ROAD statistic, the interference caused by the image edges and details in the ROAD statistic is eliminated. With the S-ROAD statistic, most of the noise pixels, including the noise at edges and details, can be distinguished. At the noise pixels filtering phase, a two-threshold iterative method is used to restore the identified noise pixels and the estimate precision is improved; thus, the image details can be efficiently preserved. Experimental results show that the proposed method provides a significant improvement over many existing filters in terms of both subjective and objective evaluations.
