Noise removal and contrast enhancement

Author(s):  
John M. Gauch
2019 ◽  
Vol 28 (10) ◽  
pp. 1950176 ◽  
Author(s):  
P. Sreelatha ◽  
M. Ezhilarasi

Informative images endure from poor contrast and noise during image acquisition. Significant information retrieval necessitates image contrast enhancement and removal of noise as a prerequisite before any further processing can be done. Dominant applications with low contrast images affected by speckle noise are medical ultrasound images. The objective of this work is to improve the effectiveness of the preprocessing stage in medical ultrasound images by enhancing the image while retaining its structural characteristics. For image enhancement, this work proposes to develop an automatic contrast enhancement technique using cumulative histogram equalization and gamma correction based on the image. For noise removal, this work proposes an algorithm Gamma Correction with Exponentially Adaptive Threshold (GCEAT) which suggests the use of GC for contrast enhancement along with a new wavelet-based adaptive soft thresholding technique for noise removal. The proposed GCEAT-based image de-noising is validated with other enhancement and noise removal techniques. Experimental results with low contrast synthetic and actual ultrasound images show that the suggested proposed system performs better than existing contrast enhancement techniques. Encouraging results were obtained with medical ultrasound images in terms of Peak-Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity Index Measure (SSIM) and Average Intensity (AI).


Author(s):  
H.T. Pearce-Percy

Recently an energy analyser of the uniform magnetic sector type has been installd in a 100KV microscope. This microscope can be used in the STEM mode. The sector is of conventional design (Fig. 1). The bending angle was chosen to be 90° for ease of construction. The bending radius (ρ) is 20 cm. and the object and image distances are 42.5 cm. and 30.0 cm. respectively.


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