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Restoration for Out-of-Focus Color Image Based on Gradient Profile Sharpness

机译:基于梯度轮廓锐度的离焦彩色图像恢复

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In color images, out-of-focus problems often occur when different wavelengths of rays are focused at different positions in the focal plane. This occurs because of lenses that have different refractive indices for different wavelengths of light. These color images in turn become blurred, and noticeable colored edges appear around objects. These misaligned edges thus degrade the overall quality of the images. In this study, we propose a restoration algorithm for misaligned edges in color images. This algorithm is based on the assumption that the gradients of color channels are highly correlated such that all edges spatially overlap in the same manner as the desired gradient. The constraint term in least squares optimization is proposed to align edges to match the desired gradient based on the transformation theory of gradient profile sharpness. The proposed constraint term adaptively uses the gradients of the channels with different weights to estimate sharp edges. We also design a new measurement to compute the energy of aligned edges in a color image. The proposed algorithm can be applied to images captured by various sensors in different environments. Experimental results show that the proposed algorithm performs effectively when estimating high-quality color images.
机译:在彩色图像中,当不同波长的光线聚焦在焦平面上的不同位置时,经常会出现失焦问题。发生这种情况的原因是,对于不同波长的光,它们的折射率不同。这些彩色图像反过来变得模糊,并且对象周围出现明显的彩色边缘。这些未对齐的边缘因此降低了图像的整体质量。在这项研究中,我们提出了一种彩色图像中边缘未对准的恢复算法。该算法基于以下假设:颜色通道的梯度高度相关,从而所有边缘都以与所需梯度相同的方式在空间上重叠。基于梯度轮廓锐度的变换理论,提出了最小二乘优化的约束项以对齐边缘以匹配所需的梯度。提出的约束项自适应地使用具有不同权重的通道的梯度来估计锐利边缘。我们还设计了一种新的度量,以计算彩色图像中对齐边缘的能量。所提出的算法可以应用于在不同环境中由各种传感器捕获的图像。实验结果表明,该算法在估计高质量彩色图像时性能良好。

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