Digital Image Processing applies efficient computer algorithms to process an image in digital computer. Different distortions occurred in image due to various reasons in image acquition, preprocessing, compression, reproduction can be removed by applying different methods like reducing noise, improving contrast etc. Image quality estimation is very widely used for many applications related to medical grounds, security related issues etc. Image quality can be measured either by Objective or Subjective methods. Mostly Peak Signal- to-Noise Ratio, Mean Squared Error, Structural Similarity Index Metric are used to estimate the quality of image using full reference objective method. Only in a few areas no reference and reduced reference are used to estimate image quality. Herein, different image quality parameters along with the image quality metrics have been reviewed. A fish bone model is proposed for expressing different estimating techniques of image quality parameters.

Image Quality; Image Quality Estimation; Image Quality Measures; Image Quality Parameters

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