Guided filter based image enhancement for focal error compensation in low cost automated histopathology microscopic system

Awasthi, N and Katare, P and Gorthi, SS and Yalavarthy, PK (2020) Guided filter based image enhancement for focal error compensation in low cost automated histopathology microscopic system. In: Journal of Biophotonics .

PDF jou_bio_2020.pdf - Published Version Restricted to Registered users only Download (27MB) | Request a copy

Abstract

Low-cost automated histopathology microscopy systems usually suffer from optical imperfections, producing images that are slightly Out of Focus (OoF). In this work, a guided filter (GF) based image preprocessing is proposed for compensating focal errors and its efficacy is demonstrated on images of healthy and malaria infected red blood cells (h-RBCs and i-RBCs), and PAP smears. Since contrast enhancement has been widely used as an image preprocessing step for the analysis of histopathology images, a systematic comparison is made with six such prominently used methods, namely Contrast Limited Adaptive Histogram Equalization (CLAHE), RIQMC-based optimal histogram matching (ROHIM), modified L0, Morphological Varying(MV)-Bitonic filter, unsharp mask filter and joint bilateral filter. The images enhanced using GF approach lead to better segmentation accuracy (upto 50 improvement over native images) and visual quality compared to other approaches, without any change in the color tones. Thus, the proposed GF approach is a viable solution for rectifying the OoF microscopy images without the loss of the valuable diagnostic information presented by the color tone. © 2020 Wiley-VCH GmbH

Item Type:	Journal Article
Publication:	Journal of Biophotonics
Publisher:	Wiley-VCH Verlag
Additional Information:	The copyright of this article belongs to Wiley-VCH Verlag
Keywords:	Blood; Costs; Error compensation; Graphic methods; Image segmentation, Contrast Enhancement; Contrast Limited Adaptive Histogram Equalization (CLAHE); Histogram matching; Image preprocessing; Malaria infected red blood cells; Microscopy systems; Segmentation accuracy; Unsharp mask filter, Image enhancement
Department/Centre:	Division of Interdisciplinary Sciences > Computational and Data Sciences Division of Physical & Mathematical Sciences > Instrumentation Appiled Physics
Date Deposited:	28 Sep 2020 08:25
Last Modified:	28 Sep 2020 08:25
URI:	http://eprints.iisc.ac.in/id/eprint/66702

Actions (login required)

View Item