Enhancement

There are 4 main methods to enhancing images Contrast/Brightness control Filtering Tools Colour Channels Large Spectral Filters NOTE:It is important to remember that when we make a change to an image we are changing all the properties of that image. This means the Bitmap and all associated descriptions of the image. SAVE THE ORIGINAL IMAGE FIRST

Enhancement Why do you wish to enhance your image? Do you want a more aesthetically pleasing image? Do you want to enhance the image to aid measurement? Do you want to see information which is present in the image but not visible?

Contrast/Brightness The first and easiest method for enhancement is using the Contrast/Brightness tool. We can alter the Brightness, Contrast and Gamma of either the whole image or individual colour channels. No change is actually made to the image until we press Apply.

Filtering Filters can be be selected from the Enhance File menu. There are various types of filters and all can be previewed in the preview window of the Filters dialog box. Convolution filters process image neighborhoods by multiplying the values within a neighborhood by a matrix of filtering coefficients called a kernel.

Types of Filters There are 3 main types of Filters Enhancement Filters - These are predominantly for aesthetic enhancement. Reduce Noise Smooth images Sharpen images Edge Filters- These are designed to pull out and enhance edges of objects within an image.

More Filters Morphological Filters- These are designed to change the shape of objects within the image Examples Erode- Erodes bright objects, Dilates dark objects Dilate- Dilates bright objects, Erodes dark objects Close- Fills gaps to connect near objects Open - Smoothes object contours Watershed - Separates touching objects

Colour channels Often Colour images contain far more information than we actually need. To simplify the image we can Convert it to monochrome -select the “Convert To” function under the Edit File Menu Extract the individual Colour channels-select the colour channel option from the process menu.

Large Spectral Filters The main problem with Convolution Filters is when using large kernels they can take a long time to process. Large Spectral Filters use algorithms that eliminate most of the multiplication and sum operations, which increases the filtering speed significantly. You can apply the filter preview to either a region of interest or to the whole image.

Large Spectral Filters LoPass: A LoPass filter removes image noise or extracts the background. HiPass: The HiPass filter increases image sharpness and contrast settings. When used with large aperture and high strength settings, this filter can perform automatic image binarization. BandPass: The BandPass filter can simultaneously reduce noise and increase image contrast, which can be very useful on low-contrast, noisy images. Edge: The Edge filters extract and enhance positive or negative edges. The Edge + filter extracts positive edges (bright features on a dark background) from an image; the Edge – filter enhances negative edges (dark features on a bright background).