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| Menu: Image > Brightness/Contrast Toolbar: Image Description: You can adjust brightness, contrast, hue, and saturation for a single or several color and grayscale images.
See also: Quick
Start "Editing color images"
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| Menu: Image > Equalize Toolbar: Image Description: This operation is applied for precise adjustment of image brightness, hue, and contrast. The command enables you to redistribute both image pixels average brightness and brightness by separate color pixel components (Red, Green, and Blue). It enables you to correct image pixel color, for example, to turn a pink background to pure white.
This dialog box represents the image histogram, displaying the averaged number of pixels, corresponding to each brightness value. The left part of histogram corresponds to low brightness value, and the right one corresponds to high brightness value (the lightest tones). The sliders in the bottom part of histogram indicate threshold values: the left black one is for the darkest value, the gray middle one is for the middle value, and the right white one is for the brightest pixel. The Levels box provides the numerical expression of current threshold values. You can select one of the four histograms: Master displays summary pixel brightness distribution, Red, Green, and Blue display distribution of the corresponding pixels color components. Using the Master histogram slides, you can proportionally modify the threshold value for all components at once. The histogram sliders Red, Green, and Blue modify brightness threshold values separately for the corresponding color component. The eyedroppers are used to select threshold values from the image The operation can be applied several times, consistently modifying an image pixel brightness distribution. See also: Quick Start "Editing color images" See also: Tutorial "Correction and Binarization of Color Images"
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| Menu: Image > AutoCorrect Toolbar: Image Description:
This operation processes an image, using a predefined set of standard operations.
See
also: Quick Start
"Enhancing Scanned Images"
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| Menu: Image > Change Size Description: This operation is used to resize an image in order to adjust its size to specified values. It may be necessary after deskewing or image cropping, and also when you obtain an image of non-standard size after scanning. If the new image size is less that the original one, the image is cropped. If the new image size is more that the original one, margins are added to the image. All changes can be observed in the preview window.
Change Size dialog contains all necessary resizing options. See also: Quick Start "Editing WiseImage objects"
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| Menu: Image > Resample Description: Resampling
is used to resize an image by modifying its resolution or size in pixels.
All three resampling methods are available in Resample dialog. See
also: Quick Start
"Editing WiseImage objects"
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| Image Clip Reset Menu: Image > Image Clip > Reset, Image > Image Clip > Rectangular, Image > Image Clip > Polygonal Description: Clipping is an operation that defines the subregion on the image for display, plotting or processing. If you save an image with a clipped area in CWS file and then reopen it, only the clipped part will be loaded thus reducing load time and saving your computer's memory. Operations such as filtering and tracing can be applied only inside the clipping boundary that protects the rest of the image from unwanted changes. You can also use the clipped area for cropping. See
also: Quick Start "Getting
started" |
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| Crop Auto Menu: Image > Crop > Auto, Image > Crop > By Frame, Image > Crop > By Rectangle, Image > Crop > By Clip Toolbar: Image Description: Family of crop operations
lets you reduce an image size to a specified rectangular image area size. You
can define this area by specifying a rectangle on the image or by specifying a
clipping boundary. You can also crop an image applying a procedure, which automatically
finds image "empty" margins and crops them.
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| Mirror by X axis Menu: Image > Mirror > By X axis, Image > Mirror > By Y axis Description: You can mirror an image about either vertical or horizontal axis crossing the image center See also: Quick
Start "Editing WiseImage objects"
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| Rotate 90-ccw Menu: Image > Rotate > 90-ccw, Image > Rotate > 180, Image > Rotate > 90-cw, Image > Rotate > Custom Angle Description: You can rotate an image about its central point using three fixed rotation angles (90, 180 and 270 degrees) or an arbitrary angle. When rotating by an arbitrary angle, the new image size automatically expands to fit the rotated image. See
also: Quick Start
"Editing WiseImage objects"
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| Menu: Image > Deskew > Auto, Image > Deskew > Manual Description: This operation enables you to correct an image skew resulting from scanning. The whole image is rotated about its central point in order to eliminate either horizontal or vertical skew. When deskewing, the new image size automatically expands to fit the deskewed image. There are three ways to deskew an image. You can define a deskew line by specifying two points in the image. This line deviation from either horizontal or vertical axis determines the skew angle. You can also deskew image by typing a skew angle in the appropriate editing box. Also, you can apply the automatic procedure of skew angle calculation See also: Quick Start "Enhancing Scanned Images" See also: Tutorial "Enhancing Raster Images"
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| Menu: Image > 4-point correction Toolbar: Image Description: Four-point correction is a simple way to eliminate trapezoid, parallelogram or projective distortions in images (technical drawings mainly). This procedure is based on the assumption that an image frame and its contents are distorted in the same way. This procedure can be used to correct image geometry if its frame has a shape of trapezium or parallelogram, rather than rectangular.
You can automatically detect page frame, specify it by mouse clicks or use preset internal page frame values (set in Tools > Preferences > Papers > Modify dialog, in Internal Frame section). See also: Quick Start "Enhancing Scanned Images" See also: Tutorial "Enhancing Raster Images"
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| Menu: Image > Calibration Toolbar: Image Description: Calibrating (also known as "rubbersheeting") eliminates arbitrary (both linear and non-linear) distortions in monochrome, grayscale, and color raster images: scanned graphic documents, geodetic plans, maps in raster format, etc. The calibration procedure transforms a raster image in such a way that
the given set of image points moves to another set of points with pre-defined
coordinates. The number of points and their locations are arbitrary. See also: Quick Start "Enhancing Scanned Images" See
also: Tutorial "Setting
up UCS, eliminating distortions using calibration"
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| Menu: Image > Binarization Toolbar: Image Description: Binarization creates monochrome raster images, containing black-and-white representation of color objects. For example, from one image of a scanned map you can extract and place to separate monochrome layers the objects of different color: isolines, roads, rivers, and other objects. Applying binarization, you create a new monochrome image of a specified color, which is placed on the specified layer. Using the specific criterion the program defines which pixels of the original (color or grayscale) image should become black (foreground pixels), and which ones should become white (background pixels), and then generates a monochrome image and places it on a new raster layer. The criterion for division of pixels into two sets is defined by the selected binarization method and its parameters (threshold values or a set of color range). The selection of pixels is controlled by the settings, specified in the Binarization dialog box.
Range
by Gray converts pixels that have gray values within all specified ranges to foreground
dots. Other pixels are converted to background dots.
Threshold
by Gray converts color pixels with brightness values above the specified level
to background dots, and pixels below this level to image dots. See also: Quick Start "Editing color images" See
also: Tutorial "Correction
and Binarization of Color Images"
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| Convert to RGB Menu: Image > Convert to > Convert to RGB, Image > Convert to > Convert to Indexed colors, Image > Convert to > Convert to Grayscale Toolbar: Image Description: By converting monochrome images to RGB or grayscale you make it possible to apply color filters to the image (Blur, Unsharp, Median). Conversion color image to 8-bit indexed is the tool facilitating color management. See also: Quick Start "Editing color images"
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| Menu: Image > Color Reduction Toolbar: Image Description: Operation that excludes image dots that fall within specified color range, i.e. categories.
In Color Reduction dialog box you can create categories and preview operation results.
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| Menu: Image > Color Separation Toolbar: Image Description: Operation that separates color image dots in non-overlapping sets, i.e. categories. It is used to extract the colors the original image was created with. The objects of one sort are usually marked with the same color; therefore you are able to separate necessary image objects. Operation places the dots of each category in a separate monochrome image. The original color image is not changed.
In Color Separation dialog box you can create categories and preview operation results. See also: Quick Start "Editing color images"
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| Menu: Image > Separation by Size Toolbar: Image Description: This operation allows you to extract raster objects with a size within a specified range onto separate layer.
See also: Quick Start "Enhancing Scanned Images" See also: Tutorial "Enhancing Raster Images"
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