CAJ | 학술논문

为了能够有效地改善低码率压缩图像的主客观质量，减少图像复原所需观测数据量，节约存储空间和计算量，提出了一种基于多层小波变换的压缩感知图像快速复原算法。该算法将压缩感知理论中的信号重构方法运用于图像复原领域，建立基于压缩感知的图像复原模型，通过少量低维投影空间的测量值并根据信号稀疏表示的先验知识对信号进行精确或高概率的复原。通过Matlab进行实验仿真，结果表明，该算法与传统的图像复原算法相比，通过相同的观测数据量可以获得更高的PSNR，复原效率也得到了提高。
위료능구유효지개선저마솔압축도상적주객관질량，감소도상복원소수관측수거량，절약존저공간화계산량，제출료일충기우다층소파변환적압축감지도상쾌속복원산법。해산법장압축감지이론중적신호중구방법운용우도상복원영역，건립기우압축감지적도상복원모형，통과소량저유투영공간적측량치병근거신호희소표시적선험지식대신호진행정학혹고개솔적복원。통과Matlab진행실험방진，결과표명，해산법여전통적도상복원산법상비，통과상동적관측수거량가이획득경고적PSNR，복원효솔야득도료제고。
In order to effectively improve both subjective and objective qualities of the compressed images with low bit rate, to reduce the data for image recovery and to save storage space and computational complexity, a fast compressed sensing image recovery algorithm based on multi-wave transform is proposed in this paper. The algorithm applies compressed sensing theory to the image recovery field, establishes recovery model and reconstructs signal accurately and efficiently from small amounts of linear measurements much fewer than its actual dimension using sparse priors of signal.Matlab is adopted for simulation. The experimental results show that the algorithm, compared with other typical reconstruction algorithm, can get higher PSNR and improve recovery efficiency when the observation data are similar.