NAME mgif - display a GIF image in monochrome SYNOPSIS mgif [ -i ] [ -v ] [ -N ] file... DESCRIPTION Mgif displays color GIF images on a monochrome ST display. GIF files carry the extensions .GIF and are compressed using LZW codes. It uses Floyd-Steinberg dithering to simulate color. In addition, this new version implements flicker palettes to simulate grayscale on a monochrome screen. All things considered, it does a decent job. Mgif now also contains numerous image processing functions to enhance images. Included are: Histogram equalization Contrast stretching Blurring Brightening (or darkening) Histogram plot Enlarge/reduce Inversion (negation with threshold) Log scaling Thresholding Median filtering Mgif allows each image processing function to be cummulative or each operation can be independent. Mgif is interactive (not a GEM program) and prompts for commands. It also has online help. OPTIONS The following command line options are recognized: -i Inquire about the file but do not display it. Output contains information like image size, number of bits per pixel, and whether or not the image is interlaced or sequential. -v Verbose output. -N Use the classic NTSC equation for computing luminescense from RGB values, that is: lum = 0.299 R + 0.587 G + 0.114 B Otherwise the values are unweighted. This option only makes sense for files with color maps in which the entry for each color uses different values for red, green, and blue. Note that the actual equation used is: lum = 0.30 R + 0.59 G + 0.11 B which is close enough. Also note that NTSC luminescense is a global option and must be set on program entry. file One or more GIF files. INTERACTIVE COMMANDS The following commands are available at the prompt: ? help Clears the screen and prints a brief summary of commands. q quit (next image) Quit does not exit the program. It just moves to the next image from the command line. ESC exit program Cleans up and exits. SPACE draw image The current image, either original or new, is drawn (or redrawn). hi histogram Plots the histogram of the original or new image. The histogram is based on intensity only. Older versions of the program displayed RGB histograms as well. That option was dropped, though it was sometimes useful. Note that if o is toggled for original image, you should toggle o again to plot a histogram of a transformed image, then toggle back to work on the original. o original/new image This toggles two sorts of behavior: 1) all transformations take place on the original image and are not cummulative, 2) all transformations take place on the new (last) image and are cummulative. n noise Adds noise not to the image but to the flicker process itself. Can help in images which have artificial banding as a result of the dithering process. You are asked for a value, which if 0, turns off noise addition. Otherwise, it is a percentage (0 to 100). Each time o is toggled, noise is reset to 0 (i.e. off). g Laplace filter This, like noise, is not applied to the image itself but rather in the flicker process. It helps to define hard edges in images and implements a Laplace filter. A quantity, Beta, is required. Use integers (1, 2, etc.) for this value. A value of 1 corresponds to Beta of 0.25, a value of 2 corresponds to Beta of 0.50, etc. A value of 0 turns off Laplace filtering. Each time o is toggled, Beta is reset to 0 (i.e. Laplace filtering off). e enlarge Enlarges images by 2x (only). s shrink Reduces images by 2x (only). Makes them half size in height and width. he histogram equalization Histogram equalization attempts to smooth out images with skewed or narrow histograms. A histogram is a graph showing the relative number of pixels with each possible intensity value. The practical use is to make images more uniform in contrast by making the histogram more uniform and hence representing all intensities as equally as possible. i inverse (negation) Invert an image, i.e. make low intensity pixels bright and visa versa. Inversion is implemented here more generally. A threshold is needed. If it is 0, the entire image is inverted. If it is a negative value between 0 and -255, only pixels below that level are inverted. If it is a positive value between 0 and 255, only pixels above that level are inverted. l log scaling Application of log scaling helps some images. It more often will sort of solarize images. t threshold (black & white) This process makes all pixels above a given threshold intensity white and all below the threshold black. It is useful in producing line art. c contrast expansion Attempts to expand the contrast of an image to cover the entire range of 256 allowable grayscales. Somewhat similar to histogram equalization but it does not redistribute actual pixels. You are asked for a threshold which is a pixel count. This determines the lowest and highest intensities, based on the histogram, which are to be stretched. br brighten (or darken) Here a constant intensity is added (or subtracted) from every pixel. A negative number causes image darkening and a positive number causes image brightening. Pixels which would otherwise go less than 0 or greater than 255 are limited to these values, respectively. bl blur Blurring an image can also help contrast, though at the expense of loss of detail. Here a 3x3 neighborhood is used. Often in practice a 5x5 neighborhood is used, but that tends to take a relatively long time. m median filter Median filtering can remove noise from an image. Here a 3x3 neighborhood is used with the median value of each of the 9 pixels replacing the pixel of interest. This is done in place so that the next pixel examined within the row or the next row will see pixels already filtered. v convolution filters Apply one of a number of 3x3 convolutions to an image. Choose one of the built-in filters (number greater than 0) or enter 0 for user defined. In the latter case, you enter the 9 elements of the convolution kernel along with a flag if there will be a multiplier (or divisor). Then enter that scaling factor. All quantities are to be integers. FILES *.gif GIF image files SEE ALSO gif(5) Gonzalez and Wintz, Digital Image Processing. Lindley, Practical Image Processing In C. Burger and Gillies, Interactive Computer Graphics. DIAGNOSTICS Various warnings attempting to isolate corrupted files. The usual messages about errors openning files, etc. If an error occurs during a processing function, the prompt line will indicate the error. NOTES Source code has standalone versions (i.e. single entry point) for both reading GIF files and displaying grayscale bitmaps with flicker. BUGS Handles images up to 400,000 bytes (hardwired) or 640x600 (or any other combination totaling 400,000). It needs dynamic memory but I generally stay away from GEMDOS Malloc(2), prefering libc malloc(3) (i.e. off stack). GIF decoding is slow and could be faster. Some of the area processes (blur, etc.) could also be faster. Log scaling needs logarithms but I did not want to use floating point so I get a crude (two significant digit) base 2 log. TODO More than I wish to consider, but here is the short list: * Output file of some sort * Zoom and pan * Rotate, mirror, etc. AUTHOR Bill Rosenkranz (rosenkra@convex.com) Flicker adopted from code by Klaus Pedersen (micro@imada.dk) VERSION mgif 3.2 91/6/3 rosenkra