Image enhancement using piecewise linear contrast stretch methods based on unsharp masking algorithms for leather image processing

Murinto, S. Winiarti, Dewi Pramudi Ismi, A. Prahara
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引用次数: 12

Abstract

This research work proposes a novel method to improve quality of animal leather images using digital image processing approach. In this work, piecewise linear contrast stretch based on unsharp masking algorithm is employed for image enhancement. The proposed method minimizes contrast problem. Experiments had been done on four categories of animal leather images namely crocodile leather, monitor lizard leather, cow leather and goat leather. The proposed method was then compared with other piecewise linear transforms based image enhancement techniques including intensity level slicing, bit plane slicing and contrast stretching methods. PSNR, MSE and SSIM values were obtained by using our proposed method and our proposed method produced better result. The values of PSNR when using piecewise linear contrast stretch unsharp masking (PLCSUS) respectively for crocodile leather, monitor lizard leather, cow leather and goat leather are 30.06 dB, 18.97 dB, 20.66 dB and 14.73 dB. This value is higher when compared to using other methods on the same image. Experiments show that our proposed method is better compared to conventional methods with respect to special characteristics of animal leather to be used as raw materials of artworks.
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基于非锐化掩蔽算法的分段线性对比度拉伸图像增强
本研究提出了一种利用数字图像处理方法提高动物皮革图像质量的新方法。本文采用分段线性对比度拉伸的非锐化掩模算法对图像进行增强。该方法最大限度地减少了对比度问题。对鳄鱼皮、巨蜥皮、牛皮和山羊皮四类动物皮革图像进行了实验。然后将该方法与其他基于分段线性变换的图像增强技术(包括强度水平切片、位平面切片和对比度拉伸方法)进行了比较。该方法得到了PSNR、MSE和SSIM值,取得了较好的结果。鳄鱼皮、巨蜥皮、牛皮和山羊皮皮采用分段线性对比拉伸不锐利掩蔽(PLCSUS)时的PSNR值分别为30.06 dB、18.97 dB、20.66 dB和14.73 dB。与在同一图像上使用其他方法相比,此值更高。实验表明,针对动物皮革作为艺术品原料的特殊性,本文提出的方法优于传统方法。
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