Enhancing Multi Exposure Images Using Convolution Neural Network

Authors(4) :-Sunitha Nandhini A, Anjani A L, Indhuja R, Jeevitha D

Due to the poor lighting condition and restricted dynamic vary of digital imaging devices, the recorded photos are usually under-/over-exposed and with low distinction. Most of the previous single image distinction improvement (SICE) strategies modify the tone curve to correct the distinction of an associated input image. Those strategies, however, typically fail in revealing image details due to the restricted data in a very single image. On the opposite hand, the SICE task is often higher accomplished if we will learn additional info from suitably collected coaching information. In this paper, we have a tendency to propose to use the convolutional neural network (CNN) to coach SICE attention. One key issue is the way to construct a coaching information set of low-contrast and high-contrast image pairs for end-to-end CNN learning. To this finish, we have a tendency to build a large-scale multi-exposure image knowledge set, that contains 589 in an elaborate way chosen high-resolution multi-exposure sequences with four, 413 images. Thirteen representatives multi-exposure image fusion and stack-based high dynamic vary imaging algorithms are accustomed urge the excellence enhanced footage for each sequence, and subjective experiments are conducted to screen the best quality one because of the reference image of every scene. With the constructed data set, a CNN can be easily trained as the SICE enhancer to improve the contrast of an under-/over-exposure image. Experimental results demonstrate the benefits of our methodology over existing SICE strategies with a major margin.

Authors and Affiliations

Sunitha Nandhini A
Assistant Professor, Department of Computer Science and Engineering, Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
Anjani A L
Department of Computer Science and Engineering Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
Indhuja R
Department of Computer Science and Engineering Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India
Jeevitha D
Department of Computer Science and Engineering Sri Krishna College of Technology, Coimbatore, Tamil Nadu, India

Single Image Contrast Enhancement, Multi-Exposure Image Fusion, Convolutional Neural Network.

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Publication Details

Published in : Volume 5 | Issue 2 | March-April 2019
Date of Publication : 2019-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 223-228
Manuscript Number : CSEIT195242
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sunitha Nandhini A, Anjani A L, Indhuja R, Jeevitha D, "Enhancing Multi Exposure Images Using Convolution Neural Network", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 5, Issue 2, pp.223-228, March-April-2019. Available at doi : https://doi.org/10.32628/CSEIT195242
Journal URL : http://ijsrcseit.com/CSEIT195242

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