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Image Contrast Enhancement using DWT-SVD based Masking Technique

机译:基于DWT-SVD的掩模技术的图像对比度增强

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A new approach based on masking technique for contrast enhancement of medical image is presented due to the low contrast characteristics. In medical image, preserving mean brightness, average information and noise factor reduction are essential to make input image more appealing visually. The proposed method incorporates spatial and frequency domain techniques to enhance the contrast of the medical image. The mask is formulated effectively between reconstructed approximation coefficients and inverse singular value decomposition (ISVD) to obtain contrast residual. Discrete wavelet transformation (DWT) and singular value decomposition (SVD) have used to decompose the input image. At last maximum contrast enhancement achieved by adding mask with the image obtained through intensity exposure histogram equalization (IEHE). The proposed approach is tested for medical images by comparing its peak signal to noise Ratio (PSNR), absolute mean brightness error (AMBE) and entropy with some existing methods and also measured in terms of visual quality.
机译:由于低对比度特征,提出了一种基于用于对比度增强的基于掩蔽技术的新方法。在医学图像中,保持平均亮度,平均信息和噪声系数减少对于在视觉上更具吸引力的输入图像至关重要。该方法包括空间和频域技术,以增强医学图像的对比度。在重建近似系数和逆奇异值分解(ISVD)之间有效地配制掩模以获得对比度残差。离散小波变换(DWT)和奇异值分解(SVD)已经用于分解输入图像。通过添加通过强度曝光直方图均衡(IEHE)获得的图像来实现通过添加掩模来实现的最大最大对比度增强。通过将其峰值信号与噪声比(PSNR)进行比较,绝对平均亮度误差(AMBE)以及具有一些现有方法的熵,并且在视觉质量方面测量,该方法测试了所提出的方法。

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