Damon M. Chandler

6.3k total citations · 3 hit papers
87 papers, 4.7k citations indexed

About

Damon M. Chandler is a scholar working on Computer Vision and Pattern Recognition, Media Technology and Cognitive Neuroscience. According to data from OpenAlex, Damon M. Chandler has authored 87 papers receiving a total of 4.7k indexed citations (citations by other indexed papers that have themselves been cited), including 80 papers in Computer Vision and Pattern Recognition, 19 papers in Media Technology and 18 papers in Cognitive Neuroscience. Recurrent topics in Damon M. Chandler's work include Image and Video Quality Assessment (41 papers), Image Enhancement Techniques (33 papers) and Advanced Image Processing Techniques (27 papers). Damon M. Chandler is often cited by papers focused on Image and Video Quality Assessment (41 papers), Image Enhancement Techniques (33 papers) and Advanced Image Processing Techniques (27 papers). Damon M. Chandler collaborates with scholars based in United States, Japan and China. Damon M. Chandler's co-authors include S.S. Hemami, Phong V. Vu, Thuong‐Cang Phan, Yi Zhang, S. Alireza Golestaneh, Eric C. Larson, Yi Zhang, David J. Field, David Field and Yi Zhang and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Transactions on Image Processing and Optics Express.

In The Last Decade

Damon M. Chandler

82 papers receiving 4.5k citations

Hit Papers

Most apparent distortion: full-reference image quality as... 2007 2026 2013 2019 2010 2007 2013 400 800 1.2k

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Damon M. Chandler United States 27 4.3k 2.1k 543 349 249 87 4.7k
Rafał Mantiuk United Kingdom 33 4.3k 1.0× 1.0k 0.5× 1.3k 2.4× 508 1.5× 305 1.2× 167 4.9k
Jinjian Wu China 32 3.5k 0.8× 2.1k 1.0× 255 0.5× 203 0.6× 174 0.7× 169 4.2k
Leida Li China 38 4.5k 1.0× 1.9k 0.9× 249 0.5× 329 0.9× 208 0.8× 241 5.1k
Nikolay Ponomarenko Ukraine 22 3.0k 0.7× 1.8k 0.8× 335 0.6× 76 0.2× 203 0.8× 115 3.2k
S.S. Hemami United States 27 5.5k 1.3× 1.2k 0.6× 260 0.5× 582 1.7× 668 2.7× 126 5.9k
Kede Ma Hong Kong 31 6.1k 1.4× 3.2k 1.5× 303 0.6× 91 0.3× 225 0.9× 67 6.7k
Muhammad Farooq Sabir United States 8 2.0k 0.5× 1.0k 0.5× 228 0.4× 71 0.2× 154 0.6× 10 2.2k
Christophe Charrier France 13 2.1k 0.5× 1.1k 0.5× 208 0.4× 77 0.2× 155 0.6× 60 2.3k
Jack Tumblin United States 21 2.7k 0.6× 1.3k 0.6× 664 1.2× 164 0.5× 46 0.2× 49 3.2k

Countries citing papers authored by Damon M. Chandler

Since Specialization
Citations

This map shows the geographic impact of Damon M. Chandler's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Damon M. Chandler with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Damon M. Chandler more than expected).

Fields of papers citing papers by Damon M. Chandler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Damon M. Chandler. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Damon M. Chandler. The network helps show where Damon M. Chandler may publish in the future.

Co-authorship network of co-authors of Damon M. Chandler

This figure shows the co-authorship network connecting the top 25 collaborators of Damon M. Chandler. A scholar is included among the top collaborators of Damon M. Chandler based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Damon M. Chandler. Damon M. Chandler is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Zhang, Yi, Damon M. Chandler, & Xuanqin Mou. (2024). Deep neural network based distortion parameter estimation for blind quality measurement of stereoscopic images. Signal Processing Image Communication. 126. 117138–117138. 1 indexed citations
2.
Zhang, Yi, et al.. (2024). Reference-Based Multi-Stage Progressive Restoration for Multi-Degraded Images. IEEE Transactions on Image Processing. 33. 4982–4997. 2 indexed citations
3.
Zhang, Yi, Damon M. Chandler, & Mikołaj Leszczuk. (2024). Retinex-based underwater image enhancement via adaptive color correction and hierarchical U-shape transformer. Optics Express. 32(14). 24018–24018. 2 indexed citations
4.
Zhang, Yi, Damon M. Chandler, & Xuanqin Mou. (2023). Deep steerable pyramid wavelet network for unified JPEG compression artifact reduction. Signal Processing Image Communication. 118. 117011–117011.
6.
Chandler, Damon M., et al.. (2023). Comparison of AR and VR memory palace quality in second-language vocabulary acquisition (Invited). Electronic Imaging. 35(10). 220–1.
7.
Chandler, Damon M., et al.. (2017). GPGPU based implementation of a high performing No Reference (NR) - IQA algorithm, BLIINDS-II. Electronic Imaging. 29(12). 21–25. 2 indexed citations
8.
Hoberock, L. L., et al.. (2016). Real-time detection of moving cast shadows using foreground luminance statistics. 5(1). 2 indexed citations
9.
Vu, Phong V. & Damon M. Chandler. (2013). Video quality assessment based on motion dissimilarity. 2 indexed citations
10.
Phan, Thuong‐Cang, et al.. (2011). ${\bf S}_{3}$: A Spectral and Spatial Measure of Local Perceived Sharpness in Natural Images. IEEE Transactions on Image Processing. 21(3). 934–945. 287 indexed citations
11.
Field, David & Damon M. Chandler. (2011). Method for estimating the relative contribution of phase and power spectra to the total information in natural-scene patches. Journal of the Optical Society of America A. 29(1). 55–55. 11 indexed citations
12.
Chandler, Damon M., et al.. (2011). On the perception of band-limited phase distortion in natural scenes. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7865. 78650C–78650C. 4 indexed citations
13.
Wang, Junle, Damon M. Chandler, & Patrick Le Callet. (2010). Quantifying the relationship between visual salience and visual importance. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 7527. 75270K–75270K. 26 indexed citations
14.
Chandler, Damon M., et al.. (2010). Image-adaptive contrast and entropy based model of regions of visible distortion. 15. 65–68. 3 indexed citations
15.
Chandler, Damon M.. (2010). Most apparent distortion: full-reference image quality assessment and the role of strategy. Journal of Electronic Imaging. 19(1). 11006–11006. 1392 indexed citations breakdown →
16.
Chandler, Damon M., et al.. (2008). Predicting the Perceived Interest of Object in Images. 20. 137–140. 1 indexed citations
17.
Chandler, Damon M. & David Field. (2007). Estimates of the information content and dimensionality of natural scenes from proximity distributions. Journal of the Optical Society of America A. 24(4). 922–922. 43 indexed citations
18.
Graham, Daniel J., Damon M. Chandler, & David J. Field. (2006). Can the theory of “whitening” explain the center-surround properties of retinal ganglion cell receptive fields?. Vision Research. 46(18). 2901–2913. 61 indexed citations
19.
Chandler, Damon M. & S.S. Hemami. (2005). Dynamic contrast-based quantization for lossy wavelet image compression. IEEE Transactions on Image Processing. 14(4). 397–410. 55 indexed citations
20.
Chandler, Damon M. & S.S. Hemami. (2003). Effects of natural images on the detectability of simple and compound wavelet subband quantization distortions. Journal of the Optical Society of America A. 20(7). 1164–1164. 53 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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