JOURNAL ARTICLE

An UM-based silhouette-crease edge enhancement for noisy images

Shwu Huey YenTai Kuang LiChun Hui Wang

Year: 2015 Journal:   International Journal of Computational Science and Engineering Vol: 10 (4)Pages: 327-327   Publisher: Inderscience Publishers

Abstract

This paper presents an improved unsharp masking (UM) technique that enhances the quality and suppresses noises for the images acquired from a noisy environment such as taken during night time. Our approach employs noise smoothing and the idea that important edges should be enhanced more than minor edges. Edges are classified as silhouette and crease edges (major and minor edges) according to their lengths. An adaptive weighting method is used to enhance the edges. In this way, the major edges (silhouette) are sharpened more than minor edges (crease). The proposed method is examined on night images as well as noisy images. It is also compared to existing UM-based methods with satisfying results.

Keywords:
Silhouette Unsharp masking Artificial intelligence Computer vision Enhanced Data Rates for GSM Evolution Smoothing Computer science Minor (academic) Weighting Masking (illustration) Image (mathematics) Mathematics Image enhancement Physics Acoustics

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Topics

Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image Processing Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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