A hybrid image restoration approach: Using fuzzy punctual kriging and genetic programming

2007 ◽  
Vol 17 (4) ◽  
pp. 224-231 ◽  
Author(s):  
Asmatullah Chaudhry ◽  
Asifullah Khan ◽  
Asad Ali ◽  
Anwar M. Mirza
Keyword(s):  
Genetic Programming ◽  
Image Restoration ◽  
Punctual Kriging

Spatially Adaptive Image Restoration Using Fuzzy Punctual Kriging

2007 ◽  
Vol 22 (4) ◽  
pp. 580-589 ◽  
Author(s):  
Anwar M. Mirza ◽  
Asmatullah Chaudhry ◽  
Badre Munir
Keyword(s):  
Image Restoration ◽  
Spatially Adaptive ◽  
Punctual Kriging

Neuro fuzzy and punctual kriging based filter for image restoration

2013 ◽  
Vol 13 (2) ◽  
pp. 817-832 ◽  
Author(s):  
Asmatullah Chaudhry ◽  
Asifullah Khan ◽  
Anwar M. Mirza ◽  
Asad Ali ◽  
Mehdi Hassan ◽  
...  
Keyword(s):  
Image Restoration ◽  
Neuro Fuzzy ◽  
Punctual Kriging

scholarly journals Genetic Programming Approach for Oral Cancer Detection and its Image Restoration

2018 ◽  
Vol Volume-2 (Issue-3) ◽  
pp. 2422-2426
Author(s):  
Rasika Joat ◽  
Dr. A. P. Thakare ◽  
Dr. Ketaki Kalele | Dr. Viashali Thakare ◽  
Keyword(s):  
Oral Cancer ◽  
Genetic Programming ◽  
Image Restoration ◽  
Cancer Detection ◽  
Programming Approach

Analysis of 3-d molecular distribution with the digital imaging microscope

1988 ◽  
Vol 46 ◽  
pp. 40-41
Author(s):  
W.A. Carrington ◽  
F.S. Fay ◽  
K.E. Fogarty ◽  
L. Lifshitz
Keyword(s):  
Image Restoration ◽  
Digital Imaging ◽  
Fluorescent Dyes ◽  
Optical Axis ◽  
Computer Hardware ◽  
Computer Algorithms ◽  
Low Contrast ◽  
Specific Proteins ◽  
Effective Use ◽  
Single Living Cells

Advances in digital imaging microscopy and in the synthesis of fluorescent dyes allow the determination of 3D distribution of specific proteins, ions, GNA or DNA in single living cells. Effective use of this technology requires a combination of optical and computer hardware and software for image restoration, feature extraction and computer graphics.The digital imaging microscope consists of a conventional epifluorescence microscope with computer controlled focus, excitation and emission wavelength and duration of excitation. Images are recorded with a cooled (-80°C) CCD. 3D images are obtained as a series of optical sections at .25 - .5 μm intervals.A conventional microscope has substantial blurring along its optical axis. Out of focus contributions to a single optical section cause low contrast and flare; details are poorly resolved along the optical axis. We have developed new computer algorithms for reversing these distortions. These image restoration techniques and scanning confocal microscopes yield significantly better images; the results from the two are comparable.

Improving x-ray map resolution with image restoration techniques

1996 ◽  
Vol 54 ◽  
pp. 598-599
Author(s):  
Richard B. Mott ◽  
John J. Friel ◽  
Charles G. Waldman
Keyword(s):  
Image Restoration ◽  
Hubble Space Telescope ◽  
Extensive Literature ◽  
Small Object ◽  
X Rays ◽  
X Ray ◽  
Mapping Parameters ◽  
The Matrix ◽  
The 1960S ◽  
Map Resolution

X-rays are emitted from a relatively large volume in bulk samples, limiting the smallest features which are visible in X-ray maps. Beam spreading also hampers attempts to make geometric measurements of features based on their boundaries in X-ray maps. This has prompted recent interest in using low voltages, and consequently mapping L or M lines, in order to minimize the blurring of the maps.An alternative strategy draws on the extensive work in image restoration (deblurring) developed in space science and astronomy since the 1960s. A recent example is the restoration of images from the Hubble Space Telescope prior to its new optics. Extensive literature exists on the theory of image restoration. The simplest case and its correspondence with X-ray mapping parameters is shown in Figures 1 and 2.Using pixels much smaller than the X-ray volume, a small object of differing composition from the matrix generates a broad, low response. This shape corresponds to the point spread function (PSF). The observed X-ray map can be modeled as an “ideal” map, with an X-ray volume of zero, convolved with the PSF. Figure 2a shows the 1-dimensional case of a line profile across a thin layer. Figure 2b shows an idealized noise-free profile which is then convolved with the PSF to give the blurred profile of Figure 2c.

Maximum image restoration in nuclear medicine

1990 ◽  
Vol 137 (3) ◽  
pp. 163 ◽  
Author(s):  
V.A. Oliveira ◽  
J.M. Nightingale
Keyword(s):  
Nuclear Medicine ◽  
Image Restoration
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