Process > Filters > 2D Filters > Large

The large spectral filters are filters of large aperture that can be used for various purposes in image processing. These filters can be applied to an ROI, active image, or active sequence. The size of the large spectral filters is not limited. All the large spectral filters are very fast regardless of the size.

When you select the Large Spectral Filters command, you will see the 2D Filters dialog box.

The main problem with large kernel filters is the slower filtering speed. Usually, the filtering process is based on the convolution of a kernel and an image. Convolution filters process image neighborhoods by multiplying the values within a neighborhood by a matrix of filtering coefficients called a kernel. The result replaces the center pixel in the image neighborhood (see Convolution filters in the previous section). The time for this filtering method increases proportionally to the size of the kernel. For kernels with sizes larger than 20-30, the process is unacceptably slow.

All filters in the Large Spectral Filters group use an algorithm that eliminates most of the multiplication and sum operations, which  increases the filtering speed significantly. In theory, the size of the filters is not limited. However, Image-Pro limits the size of the Large Spectral Filters to  4Kx 4K.

There are 5 types of  large spectral filters: Low-Pass, High-Pass, Band-Pass and two Edge filters. Each filter type has its own set of related parameters.

Low-Pass: A Low-Pass filter removes image noise or extracts the background .

• Width: Indicates the width of the filter being applied.
• Height: Indicates the height of the filter being applied.
• Passes: Indicates the number of times the filter should be applied to the image. For example, an image that has been softened by one pass of the Low-Pass filter, will be softened further by a second pass.
   

High-Pass: The High-Pass filter increases image sharpness and contrast settings. When used  with large aperture and high strength settings, this filter can perform automatic image binarization.

• Width: Indicates the width of the filter being applied.
• Height: Indicates the height of the filter being applied.
• Strength:   Enter a value from 1 - 100 that reflects how much of the filtering effect you want applied to the image.  A value of 100 specifies that you want the full strength (100%) of the filtered result applied to each pixel.  Values less than 100 cut the full weight of the filter - a value of 10 indicates that only 10% of the difference between the filtered pixel value and the original pixel value should be applied, a value of 20 indicates that 20% of the difference should be applied, and so forth.
• Passes:   Enter the number of times you want the filter applied to your image.  When a filter is applied multiple times, its effect is amplified by each pass. 
   

Band-Pass: The Band-Pass filter can simultaneously reduce noise and increase image contrast, which can be very useful on low-contrast,  noisy images. The Band-Pass filter is a combination of the Low-Pass and High-Pass filters. First an image is processed by a Low-Pass filter with a given number of passes,  and then by one pass of the High-Pass filter. The shape of a Band-Pass filter is always a square.

Filter combinations such as these allow you to suppress hi-frequency components of the image spectrum, which generally represent image noise. You may also amplify middle components of the spectrum, corresponding to the edges and fine details of various objects, and increase the contrast in these areas.

• High Size: Indicates the size of the High-Pass filter to be used for a Band-Pass filter.
• Low Size: Indicates the size of the Low-Pass filter to be used for a Band-Pass filter.
• Strength:   Enter a value from 1 - 100 that reflects how much of the filtering effect you want applied to the image.  A value of 100 specifies that you want the full strength (100%) of the filtered result applied to each pixel.  Values less than 100 cut the full weight of the filter - a value of 10 indicates that only 10% of the difference between the filtered pixel value and the original pixel value should be applied, a value of 20 indicates that 20% of the difference should be applied, and so forth.
• Passes:   Enter the number of times you want the filter applied to your image.  When a filter is applied multiple times, its effect is amplified by each pass.  An image that has been softened by one pass of the Band-Pass filter, will be softened further by a second pass.

Note: Band-Pass filters provides clearer images with smaller Low Size and more passes.

Edge: The Edge filters extract and enhance positive or negative edges. The Edge Plus filter extracts positive edges (bright features on a dark background) from an image; the Edge Minus  filter enhances negative edges (dark features on a bright background). Using non-square Edge filters,  you can create filters that will enhance either vertical or horizontal edges on the image.

• Width: Indicates the width of the filter being applied.
• Height: Indicates the height of the filter being applied.
• Strength:   Enter a value from 1 - 100 that reflects how much of the filtering effect you want applied to the image.  A value of 100 specifies that you want the full strength (100%) of the filtered result applied to each pixel.  Values less than 100 cut the full weight of the filter - a value of 10 indicates that only 10% of the difference between the filtered pixel value and the original pixel value should be applied, a value of 20 indicates that 20% of the difference should be applied, and so forth.
• Passes:   Enter the number of times you want the filter applied to your image.  When a filter is applied multiple times, its effect is amplified by each pass.  An image that has been modified by one pass of the selected filter, will be modified further by a second pass.