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all of the image data contained in the original image histogram and display it using the full range of gray-scale values from 0 to 255 using histogram stretching For example, in a bright-field image where the information might occupy a fraction of the gray-scale range, you should bring in the white and black set sliders to encompass the values contained in the histogram display If contrast needs to be improved, it is generally acceptable to eliminate signals corresponding to the top and bottom 1% of the data values Beyond that, you should consider using scaling These operations are described in 15 If bright saturating features (dead cells, precipitates) appear in the image, it is legitimate to determine the value of the brightest features in the cell of interest, and stretch the image histogram based on the revised range of pixel values.

8 9 13 13 14 14 16

If regions of an image other than the principal object show dim fluorescence, include them within the image histogram, because it is likely that there will be similar intensities in the object of interest If you exclude the unwanted intensities by stretching the histogram, the image might look posterized, leaving extensive black (or white) areas This is one of the most frequent errors made in image processing It is rarely justifiable to remove visible features of the image by adjusting the histogram just to make the picture look better This is especially true when you expect to see a signal in unwanted places because of the biology of the system or the properties of immunofluorescence labeling (Fig 16-1) Apply global processing operations conservatively.

Figure 7.29 Grasses: encoded and decoded, MPEG-2 Video (close-up)

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For routine image processing, limit yourself to 5 10% of the estimated maximum capacity of image enhancement filters such as scaling, sharpening and blurring filters, and unsharp mask operations Fortunately, there are objective criteria for thinking about this For example, in using scaling on a dark fluorescence image, it is useful to remember that a factor of 07 closely matches the logarithmic response of the eye; under bright-light conditions, contrast thresholds for adjacent objects that are barely visible vs readily distinguishable are approximately 3% and 30%, respectively The best test for whether an image has been overprocessed is to compare the processed image, side by side, with the original unprocessed image or with the real view in the microscope Image processing operations should be reported in the methods section of a research article or in the figure legend so that the reader understands how the image was manipulated.

testbed involves European NRENs and national testbeds, as well as G ANT2, crossborder dark fiber and GLIF infrastructures. A set of highly demanding applications will be adapted to prove the concept. Internationally, the project is a partner project to the US EnLIGHTened research project. Both projects will collaborate on developing a control plane for Grid computing research as well as extend functionality from each testbed to the other. The LUCIFER project is a large collaborative interdisciplinary research and testbed effort involving 20 partners from nine countries, including (a) NRENs, including CESNET (Czech Republic), PIONEIR (Poland), SURFnet (Netherlands; (b) national testbeds, including VIOLA, OptiCAT, and UKLight; (c) commercial companies, including ADVA, Hitachi, and Nortel; (d) SMEs, including NextWorks Consorzio Pisa Ricerche (CPR); and (d) research centers and universities, including Athens Information Technology Institute (AIT-Greece), Fraunhofer SCAI (Germany), Fraunhofer IMK (Germany), Fundaci i2CAT (Spain), IBBT (Belgium), RACTI (Greece), Research Centre J lich (Germany), University of Amsterdam (Netherlands), University of Bonn (Germany), University of Essex (UK), University of Wales-Swansea (UK), SARA (Netherlands), and non-EU participants, including MCNC (USA), and CCT@LSU (USA). The project is funded by the European Commission.

Avoid using extreme black and white values in the image during printing Typically the dark background around a cell in an immunofluorescence image should not be set to 0 Because halftone cells blur during printing, publishers recommend that the gray scale in submitted images not extend to true black or white The lowest value (black) should be set to 12% above 0 (30 units on an 8 bit scale), and the highest value should be set to 8% below 255 (235 on an 8 bit scale) The precise value depends on the kind of paper on which the image is to be published For high-quality paper in a journal, the bottom cut-off is about 10%; for newsprint, the value is about 20% So for newsprint, pixels with values of 50 (256 20%) and below will all appear black, even though they are easily visible on the computer screen.

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