An Improvement Algorithm for the Image Compression Imaging
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초록
Lines and textures are natural properties of the surface of natural objects, and their images can be sparselyrepresented in suitable frames such as wavelets, curvelets and wave atoms. Based on characteristics that thecurvelets framework is good at expressing the line feature and wavesat is good at representing texture features,we propose a model for the weighted sparsity constraints of the two frames. Furtherly, a multi-step iterativefast algorithm for solving the model is also proposed based on the split Bergman method. By introducingauxiliary variables and the Bergman distance, the original problem is transformed into an iterative solution oftwo simple sub-problems, which greatly reduces the computational complexity. Experiments using standardimages show that the split-based Bergman iterative algorithm in hybrid domain defeats the traditional Waveletsframework or curvelets framework both in terms of timeliness and recovery accuracy, which demonstrates thevalidity of the model and algorithm in this paper.
Abstract
Lines and textures are natural properties of the surface of natural objects, and their images can be sparselyrepresented in suitable frames such as wavelets, curvelets and wave atoms. Based on characteristics that thecurvelets framework is good at expressing the line feature and wavesat is good at representing texture features,we propose a model for the weighted sparsity constraints of the two frames. Furtherly, a multi-step iterativefast algorithm for solving the model is also proposed based on the split Bergman method. By introducingauxiliary variables and the Bergman distance, the original problem is transformed into an iterative solution oftwo simple sub-problems, which greatly reduces the computational complexity. Experiments using standardimages show that the split-based Bergman iterative algorithm in hybrid domain defeats the traditional Waveletsframework or curvelets framework both in terms of timeliness and recovery accuracy, which demonstrates thevalidity of the model and algorithm in this paper.
참고문헌 (15)
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