Wavelet domain residual proximity search for image detail enhancement

Author(s):  
Faisal Sahito ◽  
Pan Zhiwen ◽  
Junaid Ahmed ◽  
Fahad Sahito
Author(s):  
Wu Kun ◽  
Li Guiju ◽  
Han Guangliang ◽  
Yang Hang ◽  
Liu Peixun

2016 ◽  
Vol 9 (4) ◽  
pp. 423-431 ◽  
Author(s):  
郝志成 HAO Zhi-cheng ◽  
吴川 WU Chuan ◽  
杨航 YANG Hang ◽  
朱明 ZHU Ming

2012 ◽  
Vol 10 (2) ◽  
pp. 021002-21006 ◽  
Author(s):  
Bin Liu Bin Liu ◽  
Xia Wang Xia Wang ◽  
Weiqi Jin Weiqi Jin ◽  
Yan Chen Yan Chen ◽  
Chongliang Liu Chongliang Liu ◽  
...  

2014 ◽  
Vol 610 ◽  
pp. 443-448
Author(s):  
Yong Zhang ◽  
Yan Qian

Image edge details contains a rich amount of informations, enhancing edge details is the key of image post-processing. Traditional enhancement methods often lead to edge detail information lost. Fortunately, we find the curvelet transform good performance to reflect the detail information in the edge. In this paper, we add Wrap step to USFFT algorithm based on the Fast Discrete Curvelet Transform (FDCT), and adopt cyclic shift method and Er iteration. At the same time, we adopt adaptive threshold method. In order to get the objective evaluation result, comparing the wavelet algorithm and FDCT to the proposed method, we select peak signal-to-noise ratio. Experimental results show that the proposed method is not only superior to wavelet method, but also superior to single FDCT in the edge and detail information preservation.


Author(s):  
Klaus-Ruediger Peters ◽  
Eisaku Oho

Digital image acquisition and processing can provide many advantages over conventional analog image information handling, i.e., undisturbed access to the “raw data set”, quantitative analysis of the image information, and reduced costs and increased flexibility of image data handling. However, it may principally change microscopy by providing a new facility for instant exhaustive data presentation in acquired images. Detail imaging is one of the basic microscopic tasks but visual access to detail information is cumbersome and often left to post-session data analysis. A dedicated software/hardware technique is now available for automatic “near-real-time” enhancement of image detail information visually not accessible in the “raw data” image. Pertinent image details include spatial dimensions of only a few pixels in size (spatial details) and intensity variations of only a few intensity steps in height (intensity details). While conventional image enhancement techniques often produce serious image artifacts which exclude a closer inspection of enhanced detail information, the new pixel-accurate processing (PAP) technology allows instant image evaluation at an accuracy-level of the raw data through detail enhancement in full-frame images, digital zoom and noise smoothing.


2011 ◽  
Vol 31 (s1) ◽  
pp. s100504
Author(s):  
刘秀 Liu Xiu ◽  
刘斌 Liu Bin ◽  
金伟其 Jin Weiqi ◽  
范永杰 Fan Yongjie

2012 ◽  
Vol 28 (6-8) ◽  
pp. 733-742 ◽  
Author(s):  
Yun Ling ◽  
Caiping Yan ◽  
Chunxiao Liu ◽  
Xun Wang ◽  
Hong Li

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