Handbook of Image and Video Processing

By J. Gibson, A. Bovik. 2000

1,821 citations recorded by the source corpus.

Subfields: Computer Vision and Pattern Recognition, Media Technology

View Paper: https://www.semanticscholar.org/paper/72cfc2da8818b8311a163fa2979d69c0119e7147

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In Computer Vision and Pattern Recognition

In Media Technology

Citations in the corpus

Salt-and-pepper noise removal by median-type noise detectors and detail-preserving regularization (2005, background): “See [5] for instance.”
Low-Light Image Enhancement with Wavelet-Based Diffusion Models (2023, methodology): “Traditional methods mainly adopt histogram equalization (HE) [2] and Retinex theory [25] to achieve image enhancement.”
A classified and comparative study of edge detection algorithms (2002, methodology): “Edge detectors may well be classified into 5 categories as follows: 2) Zero Crossing: Which uses second derivative [5] and includes Laplacian operator and second directional derivative.”
Recent multiscale AM-FM methods in emerging applications in medical imaging (2012, methodology): “Since the AM-FM estimates of neighboring pixels could be affected by noisy estimates, a 9 × 9 median filter is often applied to the output of the IA and IF estimates (see [4,5,14]).”
Dataset Shift in Machine Learning (2009, methodology): “In the image processing literature, this is referred to as pepper noise [Bovik et al., 2000] (salt noise refers to the case when pixels values are clipped to some fixed value).”
TID2008 – A database for evaluation of full-reference visual quality assessment metrics (2004, background): “The quality evaluation of digital images is critical in many applications of image processing [1, 2].”
Fast and robust multiframe super resolution (2004, background): “The most useful property of TV criterion is that it tends to preserve edges in the reconstruction [ 22 ]–[24], as it does not severely penalize steep local gradients.”
No-Reference Image Quality Assessment in the Spatial Domain (2012, background): “, a watermark), but not the actual reference image itself, apart from the distorted image [1], [2], [3].”
Discrete Signal Processing on Graphs (2012, methodology): “Some widely-used image compression standards, such as JPEG and JPEG 2000, use orthogonal expansions implemented, respectively, by discrete cosine and wavelet transforms [60].”
Image encryption using 2D Logistic-adjusted-Sine map (2016, background): “These may change values of some image pixels and blur them [4].”
An information fidelity criterion for image quality assessment using natural scene statistics (2005, methodology): “A detailed discussion of these methods can be found in [ 3 ]‐[5].”
Comparative study of background subtraction algorithms (2010, neutral): “• median filter [5] • morphologic filter [5] • Markovian prior.”
A NEW FULL-REFERENCE QUALITY METRICS BASED ON HVS (2006, background): “Although recently in literature efforts have been made in the direction of developing quantitative image quality measures (see, e.g., [ 1 , 2, 3]), the problem is still actual.”