Citation: Tan, W.; Xu, C.; Lei, F.; Fang,
Q.; An, Z.; Wang, D.; Han, J.; Qian, K.;
Feng, B. An Endoscope Image
Enhancement Algorithm Based on
Image Decomposition. Electronics
2022, 11, 1909. https://doi.org/
10.3390/electronics11121909
Academic Editor: Pedro
Latorre-Carmona
Received: 5 June 2022
Accepted: 16 June 2022
Published: 19 June 2022
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Article
An Endoscope Image Enhancement Algorithm Based on
Image Decomposition
Wei Tan
1,2
, Chao Xu
1,2,
*, Fang Lei
3
, Qianqian Fang
1,2
, Ziheng An
1,2
, Dou Wang
1,2
, Jubao Han
1,2
, Kai Qian
1,2
and Bo Feng
1,2
1
School of Integrated Circuits, Anhui University, Hefei 230601, China; p20301226@stu.ahu.edu.cn (W.T.);
p20201087@stu.ahu.edu.cn (Q.F.); p20301227@stu.ahu.edu.cn (Z.A.); p20301228@stu.ahu.edu.cn (D.W.);
p20201029@stu.ahu.edu.cn (J.H.); p20201085@stu.ahu.edu.cn (K.Q.); p18101008@stu.ahu.edu.cn (B.F.)
2
Anhui Engineering Laboratory of Agro-Ecological Big Data, Hefei 230601, China
3
School of Humanities, Shanghai University of Finance and Economics, Shanghai 200433, China;
2019310002@live.sufe.edu.cn
* Correspondence: xchao@ahu.edu.cn; Tel.: +86-133-3919-9368
Abstract:
The visual quality of endoscopic images is a significant factor in early lesion inspection
and surgical procedures. However, due to the interference of light sources, hardware, and other
configurations, the endoscopic images collected clinically have uneven illumination, blurred details,
and contrast. This paper proposed a new endoscopic image enhancement algorithm. The image
decomposes into a detail layer and a base layer based on noise suppression. The blood vessel
information is stretched by channel in the detail layer, and adaptive brightness correction is performed
in the base layer. Finally, Fusion obtained a new endoscopic image. This paper compares the algorithm
with six other algorithms in the laboratory dataset. The algorithm is in the leading position in all five
objective evaluation metrics, further indicating that the algorithm is ahead of other algorithms in
contrast, structural similarity, and peak signal-to-noise ratio. It can effectively highlight the blood
vessel information in endoscopic images while avoiding the influence of noise and highlight points.
The proposed algorithm can well solve the existing problems of endoscopic images.
Keywords:
endoscopic images; image decomposition; image enhancement; noise suppression;
gamma correction
1. Introduction
Medical endoscopy is of great significance in early lesion screening and improving the
success rate of surgical operations. Whether it is the tracking detection of wireless capsule
endoscopy [
1
] or the high-precision surgical navigation of AR (Augmented Reality) [
2
], it is
closely related to the endoscopic image. The visual quality of endoscopic imaging is often
affected by the intricacies of the internal structure of the human body, plus factors such as
light source interference [
3
] and hardware limitations during endoscopic image acquisition,
while the cost of access to the underlying image processing side of the hardware is vast [
4
],
so we can improve the results of conventional endoscopic imaging.
Under normal circumstances, uneven illumination and low contrast are the most
critical factors affecting the clinical diagnosis of endoscopy [
5
]. At the same time, further
lesion inspection and polyp diagnosis are inseparable from high-quality endoscopic images.
To improve image quality, early researchers made a series of improvements based on
gamma correction [
6
] and a single-scale retinex [
7
] algorithm. Huang et al. [
8
] proposed
weighted adaptive gamma correction (AGCWD), which adaptively modifies the function
curve by normalizing the gamma function to achieve the effect of adaptive correction of
luminance. Jobson et al. [
9
] proposed Multi-Scale Retinex (MSRCR) with a color recovery
function to solve the phenomenon of color distortion and saturation loss arising in the
Electronics 2022, 11, 1909. https://doi.org/10.3390/electronics11121909 https://www.mdpi.com/journal/electronics
