Enhancement and segmentation of histopathological images of cancer using dynamic stochastic resonance

2020 ◽  
Vol 12 (2) ◽  
pp. 180
Author(s):  
N.A. Anuranjeeta ◽  
Shiru Sharma ◽  
Neeraj Sharma ◽  
Munendra Singh ◽  
K.K. Shukla
Keyword(s):  
Stochastic Resonance ◽  
Dynamic Stochastic Resonance ◽  
Histopathological Images ◽  
Dynamic Stochastic

Enhancement of dark and low-contrast images using dynamic stochastic resonance

2013 ◽  
Vol 7 (2) ◽  
pp. 174-184 ◽  
Author(s):  
Rajlaxmi Chouhan ◽  
Rajib Kumar Jha ◽  
Prabir Kumar Biswas
Keyword(s):  
Stochastic Resonance ◽  
Low Contrast ◽  
Dynamic Stochastic Resonance ◽  
Dynamic Stochastic

WATERMARK DETECTION USING DYNAMIC STOCHASTIC RESONANCE

2013 ◽  
Vol 12 (03) ◽  
pp. 1350010 ◽  
Author(s):  
RAJIB KUMAR JHA ◽  
APOORV CHATURVEDI ◽  
RAJLAXMI CHOUHAN
Keyword(s):  
Stochastic Resonance ◽  
Spread Spectrum ◽  
Internal Noise ◽  
External Noise ◽  
Detection Technique ◽  
Discrete Wavelet ◽  
Detection Techniques ◽  
Dynamic Stochastic Resonance ◽  
Watermark Embedding ◽  
Dynamic Stochastic

In this paper, a dynamic stochastic resonance (DSR) based watermark detection technique in discrete wavelet transform (DWT) domain is presented. Pseudo random bit sequence having certain seed value is considered as a watermark. Watermark embedding is done by embedding random bits in spread-spectrum fashion to the significant DWT coefficients. Watermark detection is quantitatively characterized by the value of correlation. The performance of watermark detection is improved by DSR which is an iterative process that utilizes the internal noise present in the image or external noise which is added during attacks. Even under various noise attacks, geometrical distortions, image enhancement and compression attacks, the DSR-based random bits detection is observed to give noteworthy improvement over existing watermark detection techniques. DSR-based technique is also found to give better detection performance when compared with the suprathreshold stochastic resonance-based detection technique.

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