EFFECTIVE FEATURE ANALYSIS COMPLETELY BLIND IMAGE QUALITY EVALUATOR

Authors

  • KRISHNA VITTHAL KHARADE M.E. Computer Science and Engineering, T.P.C.T’S C.O.E. Osmanabad, Maharashtra, India
  • MR. P.P. KALYANKAR Professor, T.P.C.T’S C.O.E. Osmanabad, Maharashtra, India

Keywords:

Blind image quality assessment, natural image statistics, multivariate Gaussian.

Abstract

In our daily lives, we accompany the digital visual information. Various distortions are introduced during the exchange, transmission or storage of this digital information. Image quality evaluation refers to the evaluation of image quality. This is because some image processing applications depend on this information. Image quality can be measured in two ways: subjective method and objective method. A subjective method is one by which human judge the image quality using average opinion scoring method (MOS). In recent years, there has been growing interest in the development of objective image quality assessment (IQA) models that not only monitor image quality degradation and reference image processing systems but also optimize various algorithms and systems, Past results are worthy of praise, but there are some important issues when applying existing IQA models to real-world applications. These include obvious things such as tasks that greatly reduce the complexity of existing IQA algorithms and are easy to use and easy to understand.

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Published

2021-03-27

Issue

Vol. 5 No. 2 (2018): IJIERT

Section

Articles

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