An integrated bilateral and unsharp masking filter for image contrast enhancement

Shi, Hongxing; Kwok, Ngaiming

doi:10.1109/icmlc.2013.6890412

Cited by 6 publications

(4 citation statements)

References 13 publications

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“…The main drawback in this unsharp masking version of the image is halo effect around the edges. This unsharp masking is implemented as [10],…”

Section: B Unsharp Masking Algorithmmentioning

confidence: 99%

“…[14]. Authors in the work [10], used the convolutional based high pass kernel to obtain high pass component from the original image.…”

Section: Proposed Systemmentioning

confidence: 99%

“…More works are prevalent for contrast enhancement with combination of unsharp masking algorithm to solve the contrast adjustment and denoising issues [8,9]. Authors proposed the integrated filter system based on combination of bilateral filter and unsharp masking in pipelined manner [10]. Image denoising and contrast enhancement are performed independently and pipelined by bilateral filter and unsharp masking filter respectively.…”

Section: Introductionmentioning

confidence: 99%

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An Unsharp Masking Algorithm Embedded With Bilateral Filter System for Enhancement of Aerial Photographs

REGAN*,

Padmavathi

2019

IJRTE

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Human visual system is more sensitive to edges and ridges in the images which composed of high spatial frequency components. Digital images having more spatial variations may contain informative content than their counterparts. Remote sensing images are one of those categories covering different aspects of land surface variations, aerial photographs are obtained on board image sensors on flying platform. Aerial photographs represent the land surfaces consists of textural and structural objects make more presence of edges. Interpolating information of aerial photographs become clumsy when the pixels are corrupted with noises at different density of levels. The kind of aerialphotographsare acquired in various way such as multi/hyper spectral sensors on board of satellites or the planes, by synthetic aperture radar (SAR) in remote sensing. The intelligence of the aerial photographs affected because of noises during image formation process and atmospheric factors. In this paper, unsharp masking (USM) algorithm based image denoising framework is proposed with Gaussian and bilateral filters. Structure similarity index(SSIM) and Image enhancement factor (IEF) based performance comparisons were studied for various noises on aerial photographs and the experimental results shown that the bilateral filter with USM system outperforms the Gaussian filter with USM. The simulation setup demonstrated using both additive and multiplicative noises with the different levels of noise density on aerial photographs.

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“…The main drawback in this unsharp masking version of the image is halo effect around the edges. This unsharp masking is implemented as [10],…”

Section: B Unsharp Masking Algorithmmentioning

confidence: 99%

“…[14]. Authors in the work [10], used the convolutional based high pass kernel to obtain high pass component from the original image.…”

Section: Proposed Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An Unsharp Masking Algorithm Embedded With Bilateral Filter System for Enhancement of Aerial Photographs

REGAN*,

Padmavathi

2019

IJRTE

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“…The classic linear unsharp masking filter (UMF) is one of the popular sharpening techniques that is capable of magnifying the high-frequency content, but it is highly sensitive to the noise present in the original image [ 15 , 16 , 24 , 25 , 26 ]. Although an algorithm combining the bilateral filter and the UMF can sharpen the edges, presented in Reference [ 27 ], the resultant images are not satisfactory enough, producing overshoot and undershoot artifacts.…”

Section: Introductionmentioning

confidence: 99%

An Improved Adaptive Spatial Preprocessing Method for Remote Sensing Images

Zheng

2021

Sensors

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Since remote sensing images are one of the main sources for people to obtain required information, the quality of the image becomes particularly important. Nevertheless, noise often inevitably exists in the image, and the targets are usually blurred by the acquisition of the imaging system, resulting in the degradation of quality of the images. In this paper, a novel preprocessing algorithm is proposed to simultaneously smooth noise and to enhance the edges, which can improve the visual quality of remote sensing images. It consists of an improved adaptive spatial filter, which is a weighted filter integrating functions of both noise removal and edge sharpness. Its processing parameters are flexible and adjustable relative to different images. The experimental results confirm that the proposed method outperforms the existing spatial algorithms both visually and quantitatively. It can play an important role in the remote sensing field in order to achieve more information of interested targets.

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Adaptive cluster-based superpixel segmentation and BMWMMBO-based DCNN classification for glaucoma detection

Sujithra,

Albert Jerome

2023

SIViP

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An integrated bilateral and unsharp masking filter for image contrast enhancement

Cited by 6 publications

References 13 publications

An Unsharp Masking Algorithm Embedded With Bilateral Filter System for Enhancement of Aerial Photographs

An Unsharp Masking Algorithm Embedded With Bilateral Filter System for Enhancement of Aerial Photographs

An Improved Adaptive Spatial Preprocessing Method for Remote Sensing Images

Adaptive cluster-based superpixel segmentation and BMWMMBO-based DCNN classification for glaucoma detection

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