Image Enhancement Using an Adaptive Un-sharp Masking Method Considering the Gradient Variation

Authors

Abstract:

Technical limitations in image capturing usually impose defective, such as contrast degradation. There are different approaches to improve the contrast of an image. Among the exiting approaches, un-sharp masking is a popular method due to its simplicity in implementation and computation. There is an important parameter in un-sharp masking, named gain factor, which affects the quality of the enhanced image. In this paper, a new adaptive un-sharp masking method is proposed. In the proposed method gradient variation of the image is used to estimate the gain factor for un-sharp masking. Gradient variation of an image can provide information about the image contrast. Subjective and objective image quality assessments are used to compare the performance of the proposed method both with the classic and the recently developed un-sharp masking methods. The experimental results show the superiority of the proposed method compared to the existing methods in image enhancing using un-sharp masking.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

Image enhancement via adaptive unsharp masking

This paper presents a new method for unsharp masking for contrast enhancement of images. The approach employs an adaptive filter that controls the contribution of the sharpening path in such a way that contrast enhancement occurs in high detail areas and little or no image sharpening occurs in smooth areas.

full text

Image Enhancement using Generalized Unsharp Masking Algorithm

Enhancement of contrast and sharpness of an image is required in many applications. Unsharp masking is a classical tool for sharpness enhancement. We propose a generalized unsharp masking algorithm using the exploratory data model as a unified framework. The proposed algorithm is designed to address three issues: 1) simultaneously enhancing contrast and sharpness by means of individual treatmen...

full text

Image Enhancement Using Adaptive Filtering

In this paper, we develop an image enhancement algorithm that modifies the local luminance mean of an image and controls the local contrast as a function of the local luminance mean of the image. The algorithm first separates an image into its lows (low pass filtered form) and highs (high pass filtered form) components. The lows component then controls the amplitude of the highs component to in...

full text

An Adaptive Image Reconstruction Method an Adaptive Image Reconstruction Method

A new adaptive regression type of image destriping method is introduced to reconstruct missing lines in mul-tispectral images. The method uses available information from the failed pixel surrounding due to spectral and spatial correlation of multispectral data. The reconstruction is based on two mutually competing adaptive regression models from which the locally optimal predictor is selected.

full text

Adaptive Unsharp Masking for Contrast Enhancement

A new scheme of unsharp masking for image contrast enhancement is presented in this paper. An adaptive algorithm is introduced so that a sharpening action is performed only in locations where the image exhibits signiicant dynamics. Hence, the ampliication of noise in smooth areas is reduced. An adaptive directional l-tering is also performed so as to provide suitable emphasis to the diierent di...

full text

buckling of viscoelastic composite plates using the finite strip method

در سال های اخیر، تقاضای استفاده از تئوری خطی ویسکوالاستیسیته بیشتر شده است. با افزایش استفاده از کامپوزیت های پیشرفته در صنایع هوایی و همچنین استفاده روزافزون از مواد پلیمری، اهمیت روش های دقیق طراحی و تحلیل چنین ساختارهایی بیشتر شده است. این مواد جدید از خودشان رفتارهای مکانیکی ارائه می دهند که با تئوری های الاستیسیته و ویسکوزیته، نمی توان آن ها را توصیف کرد. این مواد، خواص ویسکوالاستیک دارند....

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 30  issue 8

pages  1118- 1125

publication date 2017-08-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023