Gray-Scale Image Enhancement as an Automatic Process Driven by Evolution

2004 ◽  
Vol 34 (2) ◽  
pp. 1292-1298 ◽  
Author(s):  
C. Munteanu ◽  
A. Rosa
Keyword(s):  
Image Enhancement ◽  
Automatic Process ◽  
Gray Scale ◽  
Gray Scale Image

Application of image enhancement and pattern recognition algorithms to seismic reflection data

1983 ◽  
Vol 73 (1) ◽  
pp. 307-314
Author(s):  
George A. McMechan
Keyword(s):  
Pattern Recognition ◽  
Pacific Ocean ◽  
Image Enhancement ◽  
Seismic Reflection ◽  
Gray Scale ◽  
Seismic Reflection Data ◽  
Reflection Data ◽  
Recognition Algorithms ◽  
Gray Scale Image ◽  
Northeastern Pacific

abstract A digital seismic reflection section may be converted to a gray scale image composed of pixels and processed with techniques borrowed from the disciplines of image enhancement and pattern recognition. Types of processing include scaling, thresholding, density equalization, filtering, segmentation, and edge-finding. These are successfully applied to a migrated common mid-point seismic reflection line that traverses the Queen Charlotte fault (located in the northeastern Pacific Ocean). The result is the definition and enhancement of an elongated, near-vertical reflectivity anomaly associated with the Queen Charlotte fault.

scholarly journals Gray-Scale Image Dehazing Guided by Scene Depth Information

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Bo Jiang ◽  
Wanxu Zhang ◽  
Jian Zhao ◽  
Yi Ru ◽  
Min Liu ◽  
...  
Keyword(s):  
Image Enhancement ◽  
Physical Model ◽  
Color Image ◽  
Depth Information ◽  
Gray Scale ◽  
Image Dehazing ◽  
Guided Image Filter ◽  
Gray Scale Image ◽  
Novel Method ◽  
Scene Depth

Combined with two different types of image dehazing strategies based on image enhancement and atmospheric physical model, respectively, a novel method for gray-scale image dehazing is proposed in this paper. For image-enhancement-based strategy, the characteristics of its simplicity, effectiveness, and no color distortion are preserved, and the common guided image filter is modified to match the application of image enhancement. Through wavelet decomposition, the high frequency boundary of original image is preserved in advance. Moreover, the process of image dehazing can be guided by the image of scene depth proportion directly estimated from the original gray-scale image. Our method has the advantages of brightness consistency and no distortion over the state-of-the-art methods based on atmospheric physical model. Particularly, our method overcomes the essential shortcoming of the abovementioned methods that are mainly working for color image. Meanwhile, an image of scene depth proportion is acquired as a byproduct of image dehazing.

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