Literature DB >> 19211334

Morphological background detection and enhancement of images with poor lighting.

Angélica R Jiménez-Sánchez1, Jorge D Mendiola-Santibañez, Iván R Terol-Villalobos, Gilberto Herrera-Ruíz, Damián Vargas-Vázquez, Juan J García-Escalante, Alberto Lara-Guevara.   

Abstract

In this paper, some morphological transformations are used to detect the background in images characterized by poor lighting. Lately, contrast image enhancement has been carried out by the application of two operators based on the Weber's law notion. The first operator employs information from block analysis, while the second transformation utilizes the opening by reconstruction, which is employed to define the multibackground notion. The objective of contrast operators consists in normalizing the grey level of the input image with the purpose of avoiding abrupt changes in intensity among the different regions. Finally, the performance of the proposed operators is illustrated through the processing of images with different backgrounds, the majority of them with poor lighting conditions.

Mesh:

Year:  2009        PMID: 19211334     DOI: 10.1109/TIP.2008.2010152

Source DB:  PubMed          Journal:  IEEE Trans Image Process        ISSN: 1057-7149            Impact factor:   10.856


  2 in total

1.  Morphological background detection and illumination normalization of text image with poor lighting.

Authors:  Guocheng Wang; Yiwen Wang; Hui Li; Xuanqi Chen; Haitao Lu; Yanpeng Ma; Chun Peng; Yijun Wang; Linyao Tang
Journal:  PLoS One       Date:  2014-11-26       Impact factor: 3.240

2.  Improved Wallis Dodging Algorithm for Large-Scale Super-Resolution Reconstruction Remote Sensing Images.

Authors:  Chong Fan; Xushuai Chen; Lei Zhong; Min Zhou; Yun Shi; Yulin Duan
Journal:  Sensors (Basel)       Date:  2017-03-18       Impact factor: 3.576

  2 in total

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