Abstract
Abstract The images captured tend to degrade due to the scattering and absorption of light. This may be due to the diminished colors, low light and undistinguishable objects in the image. For the improvement of quality of such degraded images, Advanced Perfusion technique is employed to enhance the contrast of the low light Image. In this technique, the input image in RGB color space is converted to LAB color spaces. Two versions of input image are considered, in which, the first image is processed for brightness contrast enhancement and the second image is processed for color contrast enhancement. For the enhancement of color contrast, the second image is passed through a Recursive Separated and Weighted Histogram Equalization, (RSWHE) followed by power law transformation. Two main features are extracted from both the images, namely, Laplacian weight map and Saliency weight map. These two features of the two LAB images are fused together to produce a final enhanced image, which has improved brightness contrast and color contrast. The proposed image enhancement technique is evaluated with various performance parameters such as Structural Similarity Index (SSIM), Peak Signal-to-Noise Ratio (PSNR), and Lightness Order Error (LOE). The performance of the proposed method is then compared with the existing methods for validation.
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