A Comprehensive Survey on Image Contrast Enhancement Techniques in Spatial Domain
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A Comprehensive Survey on Image Contrast Enhancement Techniques in Spatial Domain D. Vijayalakshmi1 · Malaya Kumar Nath1 · Om Prakash Acharya2 Received: 20 February 2020 / Revised: 30 June 2020 © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Image enhancement is essential for any image processing applications. The objective of image enhancement is to reveal the hidden information which is not available for the purview of the observer due to the presence of low and poor contrast during image acquisition. The quality of the image can be raised up by increasing the contrast. Contrast enhancement has found a prominent application in various fields such as medical, satellite imaging systems owing to its better visibility of the features. In this paper, a comprehensive survey on different contrast enhancement techniques exclusively on spatial domain is presented and compared. The survey illustrates that brightness preservation, entropy preservation, structural information loss etc., are to be catered during contrast enhancement. To validate the algorithm in terms of both qualitative and quantitative means, the researchers have used various performance measures. Among all the performance measures, entropy finds the benchmark for evaluation of the algorithms. Different databases are used by researchers to analyse the performance of their algorithms, where as USC-SIPI database finds prominence in usage. Keywords Contrast enhancement · Histogram equalization · Bi-histogram equalization · 2D-histogram equalization · Performance measures
* Om Prakash Acharya [email protected] D. Vijayalakshmi [email protected] Malaya Kumar Nath [email protected] 1
National Institute of Technology Puducherry, Puducherry, India
2
Kalinga Insitute of Industrial Technology, Bhubaneswar, India
13
Vol.:(0123456789)
40
Page 2 of 40
Sensing and Imaging
(2020) 21:40
1 Introduction Contrast enhancement is the challenging area and plays a vital step in image processing applications such as medical[40], surveillance[26, 39] and machine vision fields[22, 24, 25]. The contrast of the image should be sufficient enough for clear visualization of the image. Because the information content is directly related to the contrast of the image[59]. In general, some acquired images suffer from non-uniform illumination and low contrast. Presence of light sources behind the object leads to non-uniform illuminated images. Low contrast images are due to poor dynamic range. Due to non-uniform illumination and low contrast, information content of the image is not conveyed properly which restricts from utilizing for real world applications such as character recognition, bridge painting rust defects and 2D barcodes etc.,[28]. The algorithmic view of contrast enhancement technique is to design appropriate filtering technique and modifying pixel values based on some operations on the image, which will improve the quality of the images that are apparent visual to humans. Contrast enhancement techniques are categorised t
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