A remote sensing image enhancement method using mean filter and unsharp masking in non-subsampled contourlet transform domain. (February 2017)

• Record Type: Journal Article
• Authors: Liu, Lu; Jia, Zhenhong; Yang, Jie; Kasabov, Nikola
• Is Part Of: Transactions of the Institute of Measurement and Control. Volume 39:Number 2(2017)
• Page Start: 183
• Page End: 193
• Publication Date: 2017-02
• Subjects: Image enhancement -- mean filter -- NSCT -- unsharp masking; Automatic control -- Periodicals; Measuring instruments -- Periodicals; Commande automatique -- Périodiques; Mesure -- Instruments -- Périodiques; 681.2
• DOI: 10.1177/0142331215604210
• Languages: English
• ISSNs: 0142-3312

Abstract

The intelligibility of an image can be influenced by the pseudo-Gibbs phenomenon, a small dynamic range, low-contrast, blurred edge and noise pollution that occurs in the process of image enhancement. A new remote sensing image enhancement method using mean filter and unsharp masking methods based on non-subsampled contourlet transform (NSCT) in the scope for greyscale images is proposed in this paper. First, the initial image is decomposed into the NSCT domain with a low-frequency sub-band and several high-frequency sub-bands. Secondly, linear transformation is adopted for the coefficients of the low-frequency sub-band. The mean filter is used for the coefficients of the first high-frequency sub-band. Then, all sub-bands were reconstructed into spatial domains using the inverse transformation of NSCT. Finally, unsharp masking was used to enhance the details of the reconstructed image. The experimental results show that the proposed method is superior to other methods in improving image definition, image contrast and enhancing image edges.