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Background Subtraction

Background Subtraction - Java Tutorial

Application of a suitable background subtraction algorithm is a useful technique for correcting image defects that are associated with nonuniform brightness, often (but not always) attributed to uneven illumination in the microscope. This interactive tutorial explores image processing schemes utilizing either a previously recorded background image or a processing technique that relies on the creation of a background image from the original digital image.

The tutorial initializes with a randomly selected specimen image (captured in the microscope) appearing in the left-hand window entitled Specimen Image. Each specimen name includes, in parentheses, an abbreviation designating the contrast mechanism employed in obtaining the image. The following nomenclature is used: (FL), fluorescence; (BF), brightfield; (DF), darkfield; (PC), phase contrast; (DIC), differential interference contrast (Nomarski); (HMC), Hoffman modulation contrast; and (POL), polarized light. Visitors will note that specimens captured using the various techniques available in optical microscopy behave differently during image processing in the tutorial.

Adjacent to the Specimen Image window is a window that displays either the Background Image (User-Generated or Pre-Recorded) or the Specimen Minus Background (subtraction) image. The image that is displayed is determined by the Display Image radio button panel, which is located beneath the image subtraction window. To operate the tutorial, select a specimen image from the Choose A Specimen pull-down menu. Next, select either the User-Generated Background or Pre-Recorded Background radio button from the Background Image radio button panel. To construct a custom (User-Generated; the default setting) background image, drag and drop the square control points inside of the Specimen Image window. A majority of the control points that lie on a neutral portion of the background appear cyan in color. Control points that are positioned on a lighter background region appear black in color, while control points that fall on a darker background region appear white in color.

When a specimen image is loaded using the Choose A Specimen pull-down menu, the positions of the control points will always be reset to the periphery of the specimen image. The appearance of the background image is determined by the brightness levels of the pixels contained in a neighborhood covered by the squares surrounding the control points. The Control Point Size slider can be utilized to adjust the number of pixels in each control box, ranging from 9 (3 × 3) to 81 (9 × 9), with intermediate values of 25 (5 × 5) and 49 (7 × 7). Increasing the number of pixels in the control points can often result in backgrounds that display a more even appearance. Visitors should explore repositioning the control points to create a new background image, and then examine the subtraction image that is produced by subtracting the background image from the specimen image. The best subtraction images result when control points are positioned so that the background image closely mimics that of the original specimen. Be careful to avoid placing control points on specimen regions to avoid artifacts in the resulting background subtraction image.

In transmitted light microscopy, the effects of nonuniformity in detector sensitivity and/or field illumination are often observed at very high magnification. Mottle, dirt, and a brightness gradient commonly appear in the image background, and these defects can seriously impair image contrast and mask important specimen detail. The removal of illumination defects and artifacts from images of highly magnified specimens is especially critical in video-enhanced contrast (VEC) microscopy. A method of background subtraction that is often employed in video microscopy involves capturing a background image by defocusing or by removing the specimen from the field of view. The captured background image is then repeatedly subtracted from each image that contains the specimen. In the tutorial, this technique is simulated through the Pre-Recorded Background feature, which allows the user to see the results of subtracting a pre-recorded background image from a live specimen image.

When it is not feasible to capture a background image in the microscope, a background image can be created artificially by fitting a surface function to the background of the captured specimen image. This artificial background image can then be subtracted from the specimen image. By selecting a number of points in the image that are located in the background, a list of brightness values at various positions can be obtained. The resulting information can then be utilized to obtain a least squares fit of a surface function that approximates the background. In the tutorial, eight adjustable control points are used to obtain a least squares fit of the background image with a surface function B(x, y) of the form:

B(x, y) = c0 + c1x + c2y + c3x2 + c4y2 + c5xy

where c(0) ... c(5) are the least squares solutions, and (x, y) represents the coordinates of a pixel in the fitted background image. The control points should be chosen so that they are evenly distributed across the image, and the brightness level at each control point should be representative of the background intensity. Placing many points within a small region of the image while very few or none are distributed into surrounding regions will result in a poorly constructed background image. In general, background subtraction is utilized as an initial step in improving image quality, although (in practice) additional image enhancement techniques must often be applied to the subtraction image in order to obtain a useful result.

The polynomial fitting methods explored in this tutorial can be combined with automatic histogram analysis of regions throughout the image to locate the brightest or darkest points for fitting. Alternative methods of background subtraction rely upon grayscale morphology (primarily erosion) operations to remove narrow (bright or dark) features and yield a background suitable for removal. Note that subtraction of the background from a digital image captured in the microscope is often not an appropriate processing step. Background subtraction is the method of choice for logarithmic detectors (such as analog video cameras and film), but not for linear detectors (many digital cameras and flatbed scanners), where the proper technique is to divide the image by the background.

Contributing Authors

Kenneth R. Spring - Scientific Consultant, Lusby, Maryland, 20657.

John C. Russ - Materials Science and Engineering Department, North Carolina State University, Raleigh, North Carolina, 27695.

Matthew Parry-Hill, Thomas J. Fellers and Michael W. Davidson - National High Magnetic Field Laboratory, 1800 East Paul Dirac Dr., The Florida State University, Tallahassee, Florida, 32310.

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