A comparative study of temporal phase retrieval algorithms in dynamic speckle interferometry

2012 ◽  
Author(s):  
Hao Zhang ◽  
Jin He ◽  
Meng Zhu ◽  
Zhanhua Huang
Keyword(s):  
Comparative Study ◽  
Phase Retrieval ◽  
Speckle Interferometry ◽  
Temporal Phase ◽  
Dynamic Speckle ◽  
Retrieval Algorithms

CHARACTERIZING DYNAMIC SPECKLE TIME SERIES WITH THE HURST COEFFICIENT CONCEPT

Fractals ◽  
2004 ◽  
Vol 12 (03) ◽  
pp. 319-329 ◽  
Author(s):  
L. I. PASSONI ◽  
H. RABAL ◽  
C. M. ARIZMENDI
Keyword(s):  
Speckle Pattern ◽  
Time History ◽  
Speckle Interferometry ◽  
Active Materials ◽  
Laser Illumination ◽  
Corn Seed ◽  
Dynamic Speckle ◽  
Hurst Coefficient ◽  
History Of ◽  
Living Tissues

We propose in this work a dynamic speckle descriptor based on a Hurst wavelet estimator. The dynamic speckle or biospeckle is a phenomenon produced by laser illumination of active materials, such as biological tissue or the drying process of paint. Dynamic speckle interferometry is a useful technique for assessing the time evolution of surfaces as also to segment the loci of different activity in living tissues. Considering previous biospeckle characterization based on the autocorrelation function and its relation with the Hurst coefficient, a wavelet-based estimator is proposed as a feature extraction of the dynamic speckle characteristic. Encouraging results of the descriptor performance are obtained via three different experiments: a time history of speckle pattern applied to the drying of painting, segmenting regions in whole field image applied to the viability test of a corn seed and also to the bruising in fruits.

Automatic Object Classification and Image Retrieval by Sobel Edge Detection

2014 ◽  
pp. 196-201
Keyword(s):  
Edge Detection ◽  
Comparative Study ◽  
Image Retrieval ◽  
Numerical Experiments ◽  
Object Classification ◽  
Similarity Coefficient ◽  
Cosine Similarity ◽  
Retrieval Algorithms ◽  
Sobel Edge Detection ◽  
Classification Tool

A comparative study of ability of the proposed novel image retrieval algorithms is performed to provide automated object classification invariant of rotation, translation, and scaling. Simple cosine similarity coefficient methods are analyzed. Considering applied cosine similarity coefficient methods, the two following approaches were tested and compared: the processing of the whole image and the processing of the image that contains edges extracted by the application of the Sobel edge detector. Numerical experiments on a real database sets indicate feasibility of the presented approach as an automated object classification tool without special image pre-processing.

Iterative phase retrieval algorithms Part II: Attacking optical encryption systems

2015 ◽  
Vol 54 (15) ◽  
pp. 4709 ◽  
Author(s):  
Changliang Guo ◽  
Shi Liu ◽  
John T. Sheridan
Keyword(s):  
Phase Retrieval ◽  
Optical Encryption ◽  
Retrieval Algorithms
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