ASTM E2825-2018 Standard Guide for Forensic Digital Image Processing《法医数字图像处理标准指南》.pdf
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1、Designation: E2825 12E2825 18Standard Guide forForensic Digital Image Processing1This standard is issued under the fixed designation E2825; the number immediately following the designation indicates the year oforiginal adoption or, in the case of revision, the year of last revision. A number in pare
2、ntheses indicates the year of last reapproval. Asuperscript epsilon () indicates an editorial change since the last revision or reapproval.1. Scope1.1 This guide provides digital image processing guidelines to ensure the production of quality forensic imagery for use asevidence in a court of law.1.2
3、 This guide briefly describes advantages, disadvantages, and potential limitations of each major process.1.3 This international standard was developed in accordance with internationally recognized principles on standardizationestablished in the Decision on Principles for the Development of Internati
4、onal Standards, Guides and Recommendations issuedby the World Trade Organization Technical Barriers to Trade (TBT) Committee.2. Referenced Documents2.1 ISO/IEC Standard:2ISO/IEC 10918-1:1994 Information technologyDigital compression and coding of continuous-tone still images: Requirementsand guideli
5、nes (JPEG) (also published as CCITT Recommendation T.81 (1992)2.2 SWGIT Material:3SWGDE/SWGIT Glossary SWGDE and SWGIT Digital and3.2.2 The end result is presented as a processed or working copy of the image.3.3 Avoid the introduction of artifacts that add misleading information to the image or the
6、loss of image detail that could leadto an erroneous interpretation.4. Significance and Use4.1 Processed images are used for many purposes by the forensic science community. They can yield information not readilyapparent in the original image, which can assist an expert in drawing a conclusion that m
7、ight not otherwise be reached.4.2 This guide addresses image processing and related legal considerations in the following three categories:4.2.1 Image enhancement,4.2.2 Image restoration, and4.2.3 Image compression.5. Image Enhancement5.1 Image enhancement is any process intended to improve the visu
8、al appearance of an image.5.1.1 Use brightness adjustment when the image is too bright or too dark. If the image is made too bright, there is a risk of lossof detail in light areas. If the image is made too dark, there is a risk of loss of detail in the dark areas.5.1.2 Use color processing to modif
9、y the color characteristics of objects within an image. This includes color spacetransformations, pseudocoloring, and hue and saturation adjustments.5.1.2.1 Application of these techniques can compromise the color fidelity of the image.5.1.3 Use contrast adjustment when the image lacks sufficient co
10、ntrast. If the image contrast is increased too much, there is arisk of loss of detail in both light and dark areas.5.1.4 Use cropping to remove that portion of the image that is outside the area of interest.5.1.5 Use dodging and burning to adjust brightness in localized areas.5.1.6 Use linear filter
11、ing techniques (see Fig. 1) to increase the contrast of small detail in an image. These include sharpening,blur removal, edge enhancement, and deconvolution. If a low degree of enhancement is used, the image will remain an accuraterepresentation of the scene. If a high degree of enhancement is used,
12、 the image may no longer be an accurate representation ofthe overall scene, though it still may be useful as an adjunct for interpretation of small details.5.1.6.1 A high degree of enhancement can also increase the visibility of existing noise and artifacts; examples of noise includefilm grain, snow
13、 appearing on a television screen, or random color dots.5.1.7 Use nonlinear contrast adjustments to adjust the contrast in selected brightness ranges within the image. These includegamma correction, grayscale transformation, and the use of curves or look-up tables, or both.5.1.7.1 A nonlinear contra
14、st adjustment can be used to bring out details in the shadow areas of an image without affecting thehighlight areas.5.1.7.2 A severe adjustment can cause loss of detail, color reversal, or the introduction of artifacts, or a combination thereof.(See Fig. 2.)5.1.8 Use pattern noise reduction filters
15、to identify repeating patterns in an image and selectively remove them. This type offilter can be used to remove patterns such as fabric weaves, window screens, security patterns, and halftone dots.5.1.8.1 Overuse of this technique will remove material image detail.5.1.9 Use random noise reduction t
16、echniques to reduce the contrast of small detail in the image to suppress random noise. Theseinclude such filters as low-pass filtering, Gaussian blurring, median filtering, and speckle removing.5.1.9.1 Overuse of this technique will remove material image detail.5.1.10 Use warping to change the spat
17、ial relationships among the objects in an image. It is analogous to printing a photographon a rubber sheet, then stretching the sheet in different directions, and then tacking it down. Warping can be used, for example,to remove perspective from an image or to “unroll“ a poster that was wrapped aroun
18、d a pole.5.1.10.1 Used improperly, warping can distort the natural appearance of the objects in a scene.6. Image Restoration6.1 Image restoration is any process applied to an image that has been degraded by a known cause (for example, defocus ormotion blur) to remove the effects of that degradation
19、partially or totally.E2825 1836.2 Information that has been totally lost in the image during the original imaging process cannot be replaced throughrestoration. However, partial restoration can be successful even when total restoration is impossible.FIG. 1 This Example Illustrates the Effects of Lin
20、ear FilteringLeft: Original Image, Middle: Blurred Image, and Right: Sharpened ImageFIG. 2 This Example Shows Nonlinear Contrast AdjustmentsLeft: Original Image, Middle: Enhancement of Shadow and Highlight Ar-eas at the Expense of Midrange Tones, and Right: Enhancement of Midrange Tones at the Expen
21、se of Shadow and Highlight AreasE2825 1846.3 Restoration Techniques:6.3.1 Use blur removal to remove partially or completely an image blur imposed by a known cause.6.3.1.1 Blur removal differs from the image enhancement filtering processes because the blur removal filter is designedspecifically for
22、the process that blurred the particular image under examination. Examples include defocus and motion blur, sincethese phenomena can be described mathematically. Thus, a specific filter can be designed to compensate for each blur. The degreeto which a blur can be successfully removed is limited by no
23、ise in the image, the accuracy with which the actual blurring processcan be described mathematically, and the fact that information that has been totally lost cannot be replaced. Often partial blurremoval can be successful even when total blur removal is impossible.6.3.2 Use color balancing to rende
24、r the colors in the scene more accurately. Color balancing is the extension of grayscalelinearization to a color image and the adjustment of the color components of an image. For example, a color test target havingknown colors can be placed in the scene before recording the image. Then a grayscale t
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