A Novel Tone Mapping Method for High Dynamic Range Image by Incorporating Edge-Preserving Filter Into Method Based on Retinex

Zhang, Erhu; Yang, Huiyun; Xu, Maiping

doi:10.12785/amis/010148

Cited by 3 publications

(2 citation statements)

References 1 publication

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“…However, there is a drawback of applying SSR using Gaussian filter, which is a halo artifact occurring around edges in the image. The methods for calculating the base layer using an edge-preserving filter to resolve this drawback were reported in [ 19 , 20 ]. In this work, we use an edge-preserving filter instead of a Gaussian filter, and the base layer is derived using

where p and q are pixel locations, and p = ( x , y ) and q = ( u , v ).…”

Section: Approachmentioning

confidence: 99%

TXI: Texture and Color Enhancement Imaging for Endoscopic Image Enhancement

Sato

2021

Journal of Healthcare Engineering

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Recognition of lesions with subtle morphological and/or color changes during white light imaging (WLI) endoscopy remains a challenge. Often the endoscopic image suffers from nonuniform illumination across the image due to curvature in the lumen and the direction of the illumination light of the endoscope. We propose an image enhancement technology to resolve the drawbacks above called texture and color enhancement imaging (TXI). TXI is designed to enhance three image factors in WLI (texture, brightness, and color) in order to clearly define subtle tissue differences. In our proposed method, retinex-based enhancement is employed in the chain of endoscopic image processing. Retinex-based enhancement is combined with color enhancement to greatly accentuate color tone differences of mucosal surfaces. We apply TXI to animal endoscopic images and evaluate the performance of TXI compared with conventional endoscopic enhancement technologies, conventionally used techniques for real-world image processing, and newly proposed techniques for surgical endoscopic image augmentation. Our experimental results show that TXI can enhance brightness selectively in dark areas of an endoscopic image and can enhance subtle tissue differences such as slight morphological or color changes while simultaneously preventing over-enhancement. These experimental results demonstrate the potential of the proposed TXI algorithm as a future clinical tool for detecting gastrointestinal lesions having difficult-to-recognize tissue differences.

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where p and q are pixel locations, and p = ( x , y ) and q = ( u , v ).…”

Section: Approachmentioning

confidence: 99%

TXI: Texture and Color Enhancement Imaging for Endoscopic Image Enhancement

Sato

2021

Journal of Healthcare Engineering

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show abstract

“…where (i,j) is the index for pixel position, R corresponds to the reflectance information, L is the luminance, and I = (L * G(·)) is the estimate of illumination obtained by the filtering of L with a filter G which is usually a normalized Gaussian function in the conventional works. However, it was reported that the Gaussian kernel generally makes halo artifacts near the border of bright background and dark foreground [30]. In general, the Gaussian filter needs a very large support such that the illumination estimation is less affected by reflectance values.…”

Section: B Image Decompositionmentioning

confidence: 99%

Generation of high dynamic range illumination from a single image for the enhancement of undesirably illuminated images

Park

Soh

Cho

2019

Multimed Tools Appl

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This paper presents an algorithm that enhances undesirably illuminated images by generating and fusing multi-level illuminations from a single image. The input image is first decomposed into illumination and reflectance components by using an edge-preserving smoothing filter. Then the reflectance component is scaled up to improve the image details in bright areas. The illumination component is scaled up and down to generate several illumination images that correspond to certain camera exposure values different from the original. The virtual multi-exposure illuminations are blended into an enhanced illumination, where we also propose a method to generate appropriate weight maps for the tone fusion. Finally, an enhanced image is obtained by multiplying the equalized illumination and enhanced reflectance. Experiments show that the proposed algorithm produces visually pleasing output and also yields comparable objective results to the conventional enhancement methods, while requiring modest computational loads.

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Optimal clustering based outlier detection and cluster center initialization algorithm for effective tone mapping

Neelima¹,

Kumar

2019

Multimed Tools Appl

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A Novel Tone Mapping Method for High Dynamic Range Image by Incorporating Edge-Preserving Filter Into Method Based on Retinex

Cited by 3 publications

References 1 publication

TXI: Texture and Color Enhancement Imaging for Endoscopic Image Enhancement

TXI: Texture and Color Enhancement Imaging for Endoscopic Image Enhancement

Generation of high dynamic range illumination from a single image for the enhancement of undesirably illuminated images

Optimal clustering based outlier detection and cluster center initialization algorithm for effective tone mapping

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