What are the applications of digital signal processing? Well Ideally the application is defined for the signal you are trying to process. It can be anything from audio, video, sensor output, data from the web, in short and simple words any sort of information. So processing it means making the information understandable i.e. like how discrete fourier transforms are used to understand the frequency components of a signal. Ideally DSP is thought to be about 1-D (audio, sensor output), 2-D (images and video) signal processing. Currently the hottest areas/applications in Digital Signal Processing are:
Compression: Any sort of data that can be stored in as few bits as possible with varying degrees of recoverability. Lossy or lossless.
Communication and Audio: Noise suppression/removal or speech enhancement(for audio) in these signals is always there. Plus for music applications, pushing the envelope for audiophiles is an ever present market. Better sound processors for instruments is also there.
Image and Video: This is by far the hottest market for DSP. Since you're smartphones got cameras, every company is just about megapixels, low-light clarity, HDR and all sorts of image enhancement algorithms. With the introduction of 4K video, compression is an even higher priority than before. Plus Medical imaging is the epitome of this specific sub field of DSP.
Bio-Sensors- Now you have pedometers on your smartphones, as wrist bands and as wearables. Measuring your heart rate with your smartphone camera. TI came out with a prototype to measure your SPO2 on a wristwatch. All these biometric applications are key to making healthcare more mobile for consumers.
HDMI Encoder Modulator,16in1 Digital Headend,HD RF Modulator at Soukacatv.com All these things are there in DSP. And this is just the broad applications of it. MIT is trying to extract audio by looking at the vibrations in objects And it can be done for Data Science as well. Statistical signal processing is a growing field and if you have an innate talent for statistics and like signal processing, this is the correct time to push the field for it. Digital signal processing has a wide variety of applications, including:
Audio and video compression (the quality depends on the sampling rate chosen higher sampling rate = higher quality. The file size can be compressed by applying source coding, such as Huffman coding.)
Audio signal processing (example: applying a low pass or bandpass filter to reduce external noise from an audio recording)
Image processing (example: using FFT, filtering and inverse FFT in order to remove noise from an image)
Medical applications (example: applying a histogram equalization to enhance an x-ray image)