融合Retinex和离散小波奇异值分解的远距离目标图像清晰化

针对远距离成像系统获取的低照度降质图像增强问题，提出了一种融合Retinex和离散小波奇异值分解的图像清晰化算法。该方法首先利用自适应全尺度Retinex（adaptive full-scale retinex, AFSR）“粗”提取照度分量和反射分量，然后通过离散小波变换将所提取的图像反射分量分解为4个频率子带并估计出低频子带图像的奇异值矩阵，最后应用逆小波变换“精”重建图像。实验结果表明:所提方法处理后的低照度降质图像视觉增强效果较好，在图像对比度、信息熵、平均梯度和边缘密度等客观评价指标方面优于其他经典算法。

Remote object image enhancement of fusion Retinex anddiscrete wavelet singular value decomposition

Aiming at the problem of low illumination degraded image enhancement obtained by remote imaging system, an image enhancement algorithm based on fusion Retinex and discrete wavelet singular value decomposition was proposed. In this method, the adaptive full-scale Retinex (AFSR) was used to coarsely extract the illumination and reflection components, and then the reflection components of the extracted image were decomposed into four frequency subbands by discrete wavelet transform, and the singular value matrix of the low-frequency subbands image was estimated. Finally, the inverse wavelet transform was adopted to precisely reconstruct the image. The experimental results show that the visual enhancement effect of the low illumination degraded image processed by the proposed method is better, which is superior to other classical algorithms in terms of objective evaluation indexes such as image contrast, information entropy, average gradient and edge density.