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Chung-Chou Wang

dblp:46/3593 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2008
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer graphics and multimedia
1 paper
Image and video processing · 70% Computational photography and imaging · 30%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational photography and imaging › image signal processing
color filter array		 0.112008
Demosaicing of Color Filter Array Captured Images Using Gradient Edge Detection Masks and Adaptive Heterogeneity-Projection · IEEE Trans. Image Process. 2008
Image and video processing › image restoration
demosaicing		 0.112008
Demosaicing of Color Filter Array Captured Images Using Gradient Edge Detection Masks and Adaptive Heterogeneity-Projection · IEEE Trans. Image Process. 2008
Image and video processing › image restoration › demosaicing
edge-sensing demosaicing		 0.112008
Demosaicing of Color Filter Array Captured Images Using Gradient Edge Detection Masks and Adaptive Heterogeneity-Projection · IEEE Trans. Image Process. 2008
Image and video processing › edge detection
gradient-based edge detection		 0.012008
Demosaicing of Color Filter Array Captured Images Using Gradient Edge Detection Masks and Adaptive Heterogeneity-Projection · IEEE Trans. Image Process. 2008

Methods — techniques the papers use, named apart from their topics

gradient edge detection masks · 0.1adaptive heterogeneity-projection · 0.1
YearPublicationVenuePosition
2008 Demosaicing of Color Filter Array Captured Images Using Gradient Edge Detection Masks and Adaptive Heterogeneity-Projection
abstract
Without demosaicing processing, this paper first proposes a new approach to extract more accurate gradient/edge information on mosaic images directly. Next, based on spectral-spatial correlation, a novel adaptive heterogeneity-projection with proper mask size for each pixel is presented. Combining the extracted gradient/edge information and the adaptive heterogeneity-projection values, a new edge-sensing demosaicing algorithm is presented. Based on 24 popular testing images, experimental results demonstrated that our proposed high-quality demosaicing algorithm has the best image quality performance when compared with several recently published algorithms.
Kuo-Liang Chung, Wei-Jen Yang, Wen-Ming Yan, Chung-Chou Wang
 IEEE Trans. Image Process.4