High Pass Filter

When we talk about Digital Signal Processing or Digital Image Processing Filters are the most fundamental concept. A Filter or a Digital Filter is used to sifting out the unwanted frequency response from the signals. A filter can be used to fulfill two main tasks in Digital Signal processing and those are signal separation and signal restoration. Signal separation is basically a noise separation and noise attenuation from the input signals. This process is mainly used in EKG, An electrocardiogram monitor to filter the breathing and heartbeat of the mother. Signal Restoration is a process when the input signal is distorted by any means. This is mainly used in deblurring an image. We shall look at what High Pass Filter is mainly used for. 

A High Pass Filter(HPF) main advantage is used to sharpen the image by attenuating the low frequency. When the impulse response or signal is passed through a high pass filter, an HPF mainly allows high frequencies to pass through. As High pass filters are used for sharpening the images, the frequency obtained is less compared to the cut-off frequency(ωc). In OpenCV and in digital image processing we also use HPF functionality to find the edges in an image. 

In this article, we will discuss how to implement photoshop High Pass Filter (HPF) image in Python OpenCV.