Radon-Guided Wavelet-Domain Attention U-Net for Periodic Artifact Suppression in Brain MRI. [PDF]
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A hybrid blowfish-based cryptography and chaotic quantization steganography framework with genetic key generation. [PDF]
Naveen R, Kumar AP, Roshan S.
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Force-controlled robotic ultrasound elastography enhances diagnostic consistency for thyroid nodules. [PDF]
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Retinex-based low-light image enhancement with multi-channel feature optimization. [PDF]
Wang Z, Qiao Y, Cang Y.
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Physics-Inspired Frequency-Decoupled Network for Remote Sensing Image Dehazing. [PDF]
Yang H, Chen X, Xu G.
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FSSM: Frequency-Enhanced State Space Modeling with FFT-Based Two-Sided Non-Causal Convolution for Image Dehazing. [PDF]
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PSNR Estimate for JPEG Compression
Lecture Notes in Computer Science, 2018JPEG is wildly used for image compression, which inevitably introduces some distortions, such as blocking artifacts and blurring. Peak Signal to Noise Ratio (PSNR) is the most widely used objective criterion to evaluate image distortion, which is a full reference image quality assessment and requires original image as the reference.
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Image Sharpening with Optimized PSNR
2019 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 2019A family of matrix filters are introduced through approximations to directional digital derivatives. Images can be sharpened by combining all the eight directional filtered images together. The two parameters in the filter family are determined by desired PSNR so that a given image is sharpened with optimized PSNR.
Jian-Ao Lian
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PSNR vs SSIM: imperceptibility quality assessment for image steganography
Multimedia Tools and Applications, 2020Peak signal to noise ratio (PSNR) and structural index similarity (SSIM) are two measuring tools that are widely used in image quality assessment. Especially in the steganography image, these two measuring instruments are used to measure the quality of imperceptibility.
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Mazdak Technique for PSNR Estimation in Audio Steganography
Applied Mechanics and Materials, 2012A novel method to estimate PSNR of the result of audio steganography before embedding is presented. Estimated PSNR by proposed linear interpolation formula was tested and the result was almost the same with the obtained PSNR in practical way.
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