*MATLAB CVIP Toolbox Functions*

*MATLAB CVIP Toolbox Functions*

## Transform Filters : Standard

Functions for the application of Transform filters standard are available in this category. Some of these functions require input image,spectrum,transform type,block size, frequency depending on the type of filter and they return output as image in some functions and spectrum in other functions. Related functions,included here are butterworth divided as band pass,band reject, low pass, high pass, as well as for ideal these are divided as band pass, band reject, low pass, high pass and three more function high frequency emphasis, homomorphic and h image. Ideal filters are called ideal because the transition from the passband to the stop band in the filter is perfect, it goes from 0 to 1 instantly. Although this type of filter is not realizable in physical systems. Ideal filter leaves undesirable artifacts in images. This problem can be avoided by using non ideal filter of a type called butterworth filter which does not have perfect transition. The Butterworth filters specify the order of the filter,which determines how steep the slope is in the transition of the filter function. A higher order to the filter creates a steeper slope, and the closer we get to an ideal filter,the blurring effect becomes more prominent due to the elimination of even partial high frequency information. Low pass filters tend to blur the images. They pass only low frequencies and attenuate high frequencies. They are used for image compression or for mitigating noise effects. Lowpass filtering is performed by multiplying the spectrum by a filter and then applying inverse transform to obtaion the filtered image.High pass filter will keep high freqquency information, which corresponds to areas of rapid change in brightness,such as edges and fine textures. A high pass filter can be used for edge enhancement, since it passes only high frequency information,corresponding to places where gray levels are chainging rapidly Band reject and band pass filters are specified by two cutoff frequencies, a low cutoff and a high cutoff. These filters are used in image restoration enhancement and compression. High frequency emphasis filter is a highpass filter that retains some of the low frequency information and boosts the gain of the high frequencies by including an offset value in the filter function. Homomorphic filtering is a frequency domain filtering process that compresses the brigtness,while enhancing the contrast.**butterworth_bandpass_cvip**- perform Butterworth bandpass filter**butterworth_bandreject_cvip**- perform Butterworth bandreject filter**butterworth_high_cvip**- perform Butterworth highpass filter**butterworth_low_cvip**- perform Butterworth lowpass filter**highfreqemphasis_cvip**-perform high frequency emphasis filter**homomorphic_cvip**-performs homomorphic filtering on an input**h_image_cvip**-create a mask image according to the size and type**ideal_bandpass_cvip**- perform ideal bandpass filter**ideal_bandreject_cvip**-perform ideal bandreject filter**ideal_high_cvip**-perform ideal highpass filter**ideal_low_cvip**- perform ideal lowpass filter