{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/mean-deviation-similarity-index-efficient-and","title":"Mean Deviation Similarity Index: Efficient and Reliable Full-Reference Image Quality Evaluator","arxiv_id":"1608.07433","date":"2016-08-26","proceeding":null,"authors":["Hossein Ziaei Nafchi","Atena Shahkolaei","Rachid Hedjam","Mohamed Cheriet"],"abstract":"Applications of perceptual image quality assessment (IQA) in image and video\nprocessing, such as image acquisition, image compression, image restoration and\nmultimedia communication, have led to the development of many IQA metrics. In\nthis paper, a reliable full reference IQA model is proposed that utilize\ngradient similarity (GS), chromaticity similarity (CS), and deviation pooling\n(DP). By considering the shortcomings of the commonly used GS to model human\nvisual system (HVS), a new GS is proposed through a fusion technique that is\nmore likely to follow HVS. We propose an efficient and effective formulation to\ncalculate the joint similarity map of two chromatic channels for the purpose of\nmeasuring color changes. In comparison with a commonly used formulation in the\nliterature, the proposed CS map is shown to be more efficient and provide\ncomparable or better quality predictions. Motivated by a recent work that\nutilizes the standard deviation pooling, a general formulation of the DP is\npresented in this paper and used to compute a final score from the proposed GS\nand CS maps. This proposed formulation of DP benefits from the Minkowski\npooling and a proposed power pooling as well. The experimental results on six\ndatasets of natural images, a synthetic dataset, and a digitally retouched\ndataset show that the proposed index provides comparable or better quality\npredictions than the most recent and competing state-of-the-art IQA metrics in\nthe literature, it is reliable and has low complexity. The MATLAB source code\nof the proposed metric is available at\nhttps://www.mathworks.com/matlabcentral/fileexchange/59809.","url_abs":"http://arxiv.org/abs/1608.07433v4","url_pdf":"http://arxiv.org/pdf/1608.07433v4.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"mean-deviation-similarity-index-efficient-and","repo_url":"https://github.com/photosynthesis-team/piq","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"Apache-2.0"}}],"tasks":[{"task_slug":"full-reference-image-quality-assessment","task_name":"Full reference image quality assessment"},{"task_slug":"image-compression","task_name":"Image Compression"},{"task_slug":"image-quality-assessment","task_name":"Image Quality Assessment"},{"task_slug":"image-restoration","task_name":"Image Restoration"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[{"leaderboard":"/sota/full-reference-image-quality-assessment-on-4","task":"Full reference image quality assessment","dataset":"DRIQ","model":"MDSI","rank_in_archive_order":1,"of":10,"metrics":{"PLCC":"0.8702","SRCC":"0.8508"},"uses_additional_data":false},{"leaderboard":"/sota/full-reference-image-quality-assessment-on-3","task":"Full reference image quality assessment","dataset":"ESPL","model":"MDSI","rank_in_archive_order":1,"of":11,"metrics":{"PLCC":"0.8802","SRCC":"0.8806"},"uses_additional_data":false},{"leaderboard":"/sota/full-reference-image-quality-assessment-on-2","task":"Full reference image quality assessment","dataset":"KADID10K","model":"MDSI","rank_in_archive_order":1,"of":11,"metrics":{"SRCC":"0.8853"},"uses_additional_data":false},{"leaderboard":"/sota/full-reference-image-quality-assessment-on","task":"Full reference image quality assessment","dataset":"TID2008","model":"MDSI","rank_in_archive_order":1,"of":13,"metrics":{"PLCC":"0.9160","SRCC":"0.9208"},"uses_additional_data":false},{"leaderboard":"/sota/image-quality-assessment-on-msu-fr-vqa","task":"Image Quality Assessment","dataset":"MSU FR VQA Database","model":"MDSI","rank_in_archive_order":4,"of":6,"metrics":{"SRCC":"0.8971"},"uses_additional_data":false},{"leaderboard":"/sota/video-quality-assessment-on-msu-video-quality-1","task":"Video Quality Assessment","dataset":"MSU FR VQA Database","model":"MDSI","rank_in_archive_order":13,"of":20,"metrics":{"KLCC":"0.7379","SRCC":"0.8971"},"uses_additional_data":false}],"syntology":{"syntology_url":"https://syntology.ai/paper/1608.07433","atlas_url":"https://app.syntology.ai/?focus=1608.07433","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}