Distortion compensation technique for high resolution microscopy

The paper represents the technique for distortion compensation in digital images from high resolution optical microscopes. This technique is based on approximation of necessary pixel shifts as a power function that can be identified using small set of data from distorted digital images of diffractio...

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Бібліографічні деталі
Дата:2003
Автор: Borovytsky, V.N.
Формат: Стаття
Мова:English
Опубліковано: Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України 2003
Назва видання:Semiconductor Physics Quantum Electronics & Optoelectronics
Онлайн доступ:http://dspace.nbuv.gov.ua/handle/123456789/118079
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Назва журналу:Digital Library of Periodicals of National Academy of Sciences of Ukraine
Цитувати:Distortion compensation technique for high resolution microscopy / V.N. Borovytsky // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2003. — Т. 6, № 4. — С. 517-519. — Бібліогр.: 8 назв. — англ.

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Digital Library of Periodicals of National Academy of Sciences of Ukraine
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spelling irk-123456789-1180792017-05-29T03:02:50Z Distortion compensation technique for high resolution microscopy Borovytsky, V.N. The paper represents the technique for distortion compensation in digital images from high resolution optical microscopes. This technique is based on approximation of necessary pixel shifts as a power function that can be identified using small set of data from distorted digital images of diffraction gratings. The experimental studies confirmed efficiency of the proposed technique for decreasing distortion till a level of spatial discretization. 2003 Article Distortion compensation technique for high resolution microscopy / V.N. Borovytsky // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2003. — Т. 6, № 4. — С. 517-519. — Бібліогр.: 8 назв. — англ. 1560-8034 PACS: 07.07.D.42.79.P.Q http://dspace.nbuv.gov.ua/handle/123456789/118079 en Semiconductor Physics Quantum Electronics & Optoelectronics Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
institution Digital Library of Periodicals of National Academy of Sciences of Ukraine
collection DSpace DC
language English
description The paper represents the technique for distortion compensation in digital images from high resolution optical microscopes. This technique is based on approximation of necessary pixel shifts as a power function that can be identified using small set of data from distorted digital images of diffraction gratings. The experimental studies confirmed efficiency of the proposed technique for decreasing distortion till a level of spatial discretization.
format Article
author Borovytsky, V.N.
spellingShingle Borovytsky, V.N.
Distortion compensation technique for high resolution microscopy
Semiconductor Physics Quantum Electronics & Optoelectronics
author_facet Borovytsky, V.N.
author_sort Borovytsky, V.N.
title Distortion compensation technique for high resolution microscopy
title_short Distortion compensation technique for high resolution microscopy
title_full Distortion compensation technique for high resolution microscopy
title_fullStr Distortion compensation technique for high resolution microscopy
title_full_unstemmed Distortion compensation technique for high resolution microscopy
title_sort distortion compensation technique for high resolution microscopy
publisher Інститут фізики напівпровідників імені В.Є. Лашкарьова НАН України
publishDate 2003
url http://dspace.nbuv.gov.ua/handle/123456789/118079
citation_txt Distortion compensation technique for high resolution microscopy / V.N. Borovytsky // Semiconductor Physics Quantum Electronics & Optoelectronics. — 2003. — Т. 6, № 4. — С. 517-519. — Бібліогр.: 8 назв. — англ.
series Semiconductor Physics Quantum Electronics & Optoelectronics
work_keys_str_mv AT borovytskyvn distortioncompensationtechniqueforhighresolutionmicroscopy
first_indexed 2025-07-08T13:19:46Z
last_indexed 2025-07-08T13:19:46Z
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fulltext 517© 2003, V. Lashkaryov Institute of Semiconductor Physics, National Academy of Sciences of Ukraine Semiconductor Physics, Quantum Electronics & Optoelectronics. 2003. V. 6, N 4. P. 517-519. PACS: 07.07.D.42.79.P.Q Distortion compensation technique for high resolution microscopy V.N. Borovytsky Information Software Systems Ltd, 15 Bozhenko str., 03680 Kyiv, Ukraine Abstract. The paper represents the technique for distortion compensation in digital images from high resolution optical microscopes. This technique is based on approximation of necessary pixel shifts as a power function that can be identified using small set of data from distorted digital images of diffraction gratings. The experimental studies confirmed efficiency of the proposed technique for decreasing distortion till a level of spatial discretization. Keywords: distortion, optical microscope, digital image, pixel shift. Paper received 20.11.03; accepted for publication 11.12.03. 1. Introduction Optical microscopy has a wide field of applications in- cluding medicine, material science, semiconductor indus- try, machine building and etc [1,2]. Implementation of digital cameras and image processing software is one of the most perspective tendencies in optical microscopy [1]. Digital cameras installed on microscopes and attached to personal computers with image processing software make possible fast and effective capturing, saving, trans- mitting and processing of digital images [1]. Modern digital cameras have more than million pho- tosensitive cells that are located with sub-micron accu- racy in image plane of a microscope [3]. Thus small im- age corruptions caused by distortion of microscope op- tics become visible in digital images even a human ob- server can not see these small distortion. Good micro- scope optics has distortion in range 1�2 % and it can dramatically reduce precision of measuring locations and dimensions of large objects in digital images [2]. Thus the problem of distortion compensation becomes actual for optical microscopy. 2. Analysis of known techniques for distortion compensation The known techniques for distortion compensation are based on operations like pixel shifts depending on pixel coordinates [4�6]. The necessary shifts are calculated using a distorted images of two dimensional periodical test-objects � grids, matrices of circles, boxes, points and etc. But direct application of these techniques for high resolution optical microscopy is difficult. First, two di- mensional test-objects with micron dimensions of elements and sub-micron accuracy of their locations are extremely expensive and they are not widely used in microscopy laboratories. Second, digital images produced by opti- cal microscopes have sufficient non-uniformity of inten- sity distribution. It introduces errors in binarization of a whole digital image and as a results pixel shift value can not be calculated for each pixel in a digital image. Third, for calculation of necessary pixel shifts and their appli- cation to digital images a user has to purchase the expen- sive software packages for microscopy such as Image Pro, Clemex, ASIS, Matrox Image Library and the others. Due to the mentioned reasons the distortion compensa- tion using the known techniques becomes expensive and complicated procedure. 3. The proposed technique for distortion com- pensation To overcome the disadvantages of the known techniques the new interesting approach has been found. The core idea of this approach is identification of pixel shift func- tion using a small set of data from distorted images of a diffraction gratings. This pixel shift function in form of a displace mask for Adobe PhotoShop can be implemented to distorted images to reduce distortion [4,7]. The com- pensation procedure requires the following operations: 518 SQO, 6(4), 2003 V.N. Borovytsky: Distortion compensation technique for high resolution microscopy 1. A set of digital images of vertical and horizontal diffraction gratings has to be prepared. The diffraction gratings with spatial periods of 300�1000 lines per mm are widely used in optical laboratories. They are not very expensive and they have sub-micron accuracy of line width, pitch and location. 2. The center zone in these images is considered as a reference one. In this zone an average value of spatial period of gratings in number of pixels can be calculated. It has to note that distortion appears in boundary zones of digital images [2, 4, 8]. The central zone of image can be considered as a zone without distortion. 3. For the boundary zone necessary pixels shifts should be identified for a number of pixels. These pixel shifts are equal to difference of pixel coordinated in a dis- torted digital image and in a non distorted one (Fig. 1): ( ) ( ) ,, 1, O O O ypnyyyxy x pn y xx y y xxyxx Y Y −⋅=−=∆ ⋅    − ⋅ =−⋅=−=∆ (1) where ∆x(x,y) , ∆y(x,y) � the necessary pixel shifst as a function of pixel coordinates in a distorted digital image, x, y � the coordinates of the pixel in a distorted digital image, xO, yO � the coordinates of the pixel in a non-dis- torted digital image, n, pY � the number of lines from a center of the digital image till the point (x,y) and the average value of spatial period in pixel of grating (Fig. 1). 4. The pixel shift function can be identified using the set of data about necessary pixel shifts in various pixels of digital images. The best fit power function is good formula for approximation of the pixel shift function be- cause according to optical theory the geometrical distor- tion can be characterized by a power function with axial symmetry [8]. It is obvious that this axial symmetry re- mains only in case of square shape of photosensitive cells and equal spatial periods along axises OX and OY in a digital camera. The regression analysis of the data (1) helps to calculate the parameters of the pixel shift func- tions: ( ) ( ) PB PA d yx Byxy d yx Ayxx         + ⋅⋅=∆         + ⋅⋅=∆ 22 22 2, 2, (2) where A, B, PA, PB � the parameters of the pixel shift functions that have to be calculated during search the best fit function for the data set (1), d � diagonal of a digital image: 22 MM yxd += xM, yM � the dimensions of a digital image in pixels. 5. The pixel shift functions (2) can be represented in form of a pixel displace mask for the widely used image processing software package Adobe PhotoShop [7]. This displace mask uses different color channels for coding necessary pixel shifts in horizontal and vertical direc- tions: ( )( ) ( )( ) 255 5.0,5.0128int 5.0,5.0128int , , , = ⋅−⋅−∆⋅+= ⋅−⋅−∆⋅+= ji MMji MMji b yyxxykg yyxxxkr (3) where ri,j , gi,j , bi,j � the color values of i, j � pixels of 24- bit color displace mask for distortion compensation [7], i, j � the pixel coordinates, k � the coefficient for getting values in range [�128, +128], int( ) � the function for conversion of real values into integer ones. Generation of a pixel displace mask (3) can be done by any mathematical software packages such as MathCAD, MatLab only once for each combination of a microscope optics and a digital camera. 6. The generated displace mask (3) has to be applied to the distorted digital images. Adobe PhotoShop makes this operation quickly. This operation can be easily ap- plied for a set of distorted digital images. ( ( x x O, , y y O) ) Fig. 1. Digital images of gratings with distortion (dark color) and without it (bright color). The pixel coordinates (x, y) in a distorted image correspond to the pixel coordinates (xO, yO) in a non-distorted one, data for distortion compensation is done by collection of this information from various pixels marked as black points in a distorted image. V.N. Borovytsky: Distortion compensation technique for high resolution microscopy 519SQO, 6(4), 2003 Conclusions The proposed distortion compensation techniques is based on identification of pixel shift function using a small set of data from distorted digital images of diffraction gratings (1�3). The experimental studies have confirmed that this technique makes possible to reduce a geometri- cal distortion in high resolution microscopy from 0.6 % till 0.055 % (Fig. 2). References 1. W. G. Hand, A practical guide to digital microscopy // Photonics Spectra, No10. p.100-104 (2001). 2. G.E. Skvortzov, V.A. Panov, N.I. Polakov, L.A. Fedin, Mic- roscopes. � L.: Mashinostroenie, 1969. 3. B. L. Benamati, In search of ultimate Image Sensor // Photonics Spectra, No 9. p. 132�136 (2001). 4. Harri Ojanen, Automatic coorection of Lens distortion using digital image processing // Preprint of the State University of New Jersey, Mathematical department, Rutgers. Preprint lo- cation is www.math.rutgers.edu/~ojanen/ 5. X. Wang, R. Ning, Accurate and efficient image intensifier distortion correction algorithm for volume tomo graphic angionaphy // Optical Engineering, 37(3). p. 997-983 (1998). 6. V. Krzyzanek, Analysis of continiously distortted quasi-peri- odic images: two-dimensional reconstruction of S-layers of cyanobacteria // Optical Engineering, 39(4), p. 872-878 (2000). 7. A.D.Greenberd, S.Greenberd, Fundamental PhotoShop, Berkeley: Osborne McGraw-Hill, 1997. 8. B.N. Begynov, N.P. Zakaznov, Theory of optical systems. � M.: Mashinostroenie, 1973. a b Fig. 2. Boundary fragments of digital images before (a) and after (b) distortion compensation (fragment dimensions in pixels � width 3040×height 230 � corresponds to a field in an object plane � 0.23×0.018 mm, image fragments are scaled in horizontal direc- tion to make distortion 0.6 % visible, a black reference lines indicates how gratings images differs from straight lines before and after distortion compensation).