Edge enhancement of phase objects using a cyclic-path polarization interferometer

2015 ◽  
Author(s):  
Sonali Chakraborty ◽  
K. Bhattacharya
2014 ◽  
Vol 53 (4) ◽  
pp. 727 ◽  
Author(s):  
Sonali Chakraborty ◽  
K. Bhattacharya

2016 ◽  
Vol 55 (21) ◽  
pp. 5634 ◽  
Author(s):  
Sonali Chakraborty ◽  
K. Bhattacharya

2012 ◽  
pp. 122-144 ◽  
Author(s):  
O. Bessonova

This article analyzes the formation of the Russian institutional matrix with regard to its previous development, but in line with the laws of economic evolution. The structure and development of an razdatok-type institutional matrix on three institutional cycles is considered. It is shown that in transformationphases the market institutional matrix masking the quasi-market is used. The author concludes that system crises could be overcome due to the mutual substitution of the two types of institutional matrices, and the cyclic path of Russias development became a consequence of that. The paper claims that the current institutional matrix will provide transition to a new level of high-quality growth only in case of synthesis of market and razdatok mechanisms.


1991 ◽  
Vol 7 (5-6) ◽  
pp. 232-246 ◽  
Author(s):  
A. J. Cole
Keyword(s):  

2013 ◽  
Vol 2013 ◽  
pp. 1-21 ◽  
Author(s):  
Asloob Ahmad Mudassar ◽  
Saira Butt

A variety of blood vessel extraction (BVE) techniques exist in the literature, but they do not always lead to acceptable solutions especially in the presence of anomalies where the reported work is limited. Four techniques are presented for BVE: (1) BVE using Image Line Cross-Sections (ILCS), (2) BVE using Edge Enhancement and Edge Detection (EEED), (3) BVE using Modified Matched Filtering (MMF), and (4) BVE using Continuation Algorithm (CA). These four techniques have been designed especially for abnormal retinal images containing low vessel contrasts, drusen, exudates, and other artifacts. The four techniques were applied to 30 abnormal retinal images, and the success rate was found to be (95 to 99%) for CA, (88–91%) for EEED, (80–85%) for MMF, and (74–78%) for ILCS. Application of these four techniques to 105 normal retinal images gave improved results: (99-100%) for CA, (96–98%) for EEED, (94-95%) for MMF, and (88–93%) for ILCS. Investigations revealed that the four techniques in the order of increasing performance could be arranged as ILCS, MMF, EEED, and CA. Here we demonstrate these four techniques for abnormal retinal images only. ILCS, EEED, and CA are novel additions whereas MMF is an improved and modified version of an existing matched filtering technique. CA is a promising technique.


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