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Distortion effects on image quality evaluation and classification

Author: YeXiaoQiong
Tutor: LiuWenYu
School: Huazhong University of Science and Technology
Course: Communication and Information System
Keywords: Image Quality Assessment Image distortion Blocking effect Ringing effects Support Vector Machine Machine Learning
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 74
Quote: 0
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Abstract


Objective image quality assessment is a classic research topic , the goal is to give the human eye and the subjective evaluation of consistent results , according to the evaluation process, whether a reference chart is divided into three methods : full- reference evaluation , semi- reference evaluation and without reference evaluation . No reference evaluation because no reference map, and has broad application prospects. Existing non- reference image quality assessment is often assumed that the image distortion caused by the degradation process is known, this is a very restrictive assumption because in practice are often not aware of what the image is the result of the degradation process . This paper presents an image-based distortion effects appear in the non- reference image quality assessment method does not require a priori information during image distortion , and truly no reference. The method analyzes the impact of the digital image quality common four distortion effects : blur , noise, blocking effect and ringing effect, and were characterized by extracting the underlying measure of four kinds of image distortion effects , the final quality of the image distortion effects for each measure value and a weighted Minkowski , weight training to get through subjective database . This paper also presents a variety of distortion effects of image classification method . The image processing performance through different distortion effects are different, the various effects of the measure as a feature vector , using support vector machine classification model is trained to obtain . Although only consider the JPEG compression , JPEG2K compression , noise , Gaussian blur four kinds of image degradation process, but the process by extending the type of distortion effects may occur , the method can be extended to any digital image processing . Both methods require training to get through subjective database model is based on machine learning methods .

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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