Results 231 to 240 of about 75,390 (291)

FSSM: Frequency-Enhanced State Space Modeling with FFT-Based Two-Sided Non-Causal Convolution for Image Dehazing. [PDF]

J Imaging
Zeng L, Huang Y.
europepmc   +1 more source

Retinex-based low-light image enhancement with multi-channel feature optimization. [PDF]

Sci Prog
Wang Z, Qiao Y, Cang Y.
europepmc   +1 more source

Physics-Inspired Frequency-Decoupled Network for Remote Sensing Image Dehazing. [PDF]

Sensors (Basel)
Yang H, Chen X, Xu G.
europepmc   +1 more source

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PSNR vs SSIM: imperceptibility quality assessment for image steganography

Multimedia Tools and Applications, 2020
Peak 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.
De Rosal Ignatius Moses Setiadi
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A Simple Relationship Between SSIM and PSNR for DCT-Based Compressed Images and Video: SSIM as Content-Aware PSNR

2023 IEEE 25th International Workshop on Multimedia Signal Processing (MMSP), 2023
The aim of this paper is to show how the structural similarity metric SSIM for image quality assessment can be seen in many cases, such as DCT-based compressed images and video, as a content-aware version of the peak signal-to-noise ratio (PSNR). In fact,
Maria G. Martini
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Image Quality Metrics: PSNR vs. SSIM

2010 20th International Conference on Pattern Recognition, 2010
In this paper, we analyse two well-known objective image quality metrics, the peak-signal-to-noise ratio (PSNR) as well as the structural similarity index measure (SSIM), and we derive a simple mathematical relationship between them which works for various kinds of image degradations such as Gaussian blur, additive Gaussian white noise, jpeg and ...
Alain Horé, Djemel Ziou
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Image Sharpening with Optimized PSNR

2019 IEEE International Conference on Signal and Image Processing Applications (ICSIPA), 2019
A 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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Color-Sensitivity-Based Combined PSNR for Objective Video Quality Assessment

IEEE Transactions on Circuits and Systems for Video Technology, 2019
The peak signal-to-noise ratio (PSNR) has been widely employed as an objective video quality assessment (VQA) metric. Usually, videos are represented in the YCbCr color space, which results in three PSNR values for each video frame.
Xiwu Shang, Jie Liang, Guozhong Wang
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IV-PSNR—The Objective Quality Metric for Immersive Video Applications

IEEE Transactions on Circuits and Systems for Video Technology, 2022
This paper presents a new objective quality metric that was adapted to the complex characteristics of immersive video (IV) which is prone to errors caused by processing and compression of multiple input views and virtual view synthesis.
Adrian Dziembowski, Dawid Mieloch, Jakub Stankowski, Adam Grzelka   +3 more
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PSNR Estimate for JPEG Compression

Lecture Notes in Computer Science, 2018
JPEG 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.
Ci Wang
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