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中文摘要：
传统的数据采集都要遵循奈奎斯特采样定理的两倍以上带宽取样，而压缩感知理论突破原有采样定理的限制，为从少量数据重建原始数据提供了可能性。提出了基于JND压缩感知的稳健性图像编码方法，该新方法将压缩感知理论应用于图像编码，并引入JND模型来提高信号的稀疏性。实验结果表明，提出的方法大大降低了压缩感知的重建时间，同时也提高了图像的重建质量。
英文摘要：
The traditional data acquisition is under Nyquist sampling theorem, that is,samphng rate must De at least twice mc signal bandwidth. However, compressive sensing broke through the original sampling theorem, whict, provides a possibility for original data recovery from a small amount of data. A method of compressive sensing image robust encoding based on JND model is proposed. Compressive sensing theorem is applied to image coding combined JND model, which improves the sparsity of image signal. Experimental results demonstrate that the proposed method reduces recovery time of compressive sensing greatly, and improves the image quality.
同期刊论文项目
同项目期刊论文
Stereoscopic Visual Attention Based Regional Bit Allocation Optimization for Multi-view Video Coding
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