The 11th Iranian and the first International Conference on Machine Vision and Image Processing

A Weighted, Statistical Based, No-Reference Metric for Holography Image Quality Assessment

Vahid Hajihashemi, Mohammad Mehdi Arab Ameri, Abdoreza Alavi Gharahbagh, Hassan Pahlouvary
The 11th Iranian and the first International Conference on Machine Vision and Image Processing (MVIP 2020)

Abstract

Digital holography is one of the 3D imaging systems that suffer Speckle noise. With respect to the importance of quality in 3D images, we develop an efficient general-purpose blind/no-reference holography image quality assessment metric for evaluating the quality of digital holography images. The main novelty of our approach to blind image quality assessment is based on the hypothesis that each digital holography has statistical properties that are changing in the presence of speckle noise. This change can be measured by some full reference metrics that are applied to input image and a new image, which were made by adding a known level of speckle noise to input image. These full reference measurements have the ability of identifying the distortion afflicting the input image and perform a no-reference quality assessment. In fact, adding noise to input image leads to quality loss, and the value of this loss give information about the input image quality. Finally, the result of the proposed method in estimating the quality of digital holography images were compared with some well-known full reference methods in order to demonstrate its ability.

Keywords: Quality Assessment, Denoising, DE-speckling, Analyzing



© 2017-2021 ISMVIP All Rights Reserved