Digital Image Processing

Introduction to digital image processing (DIP) and its applications, image sensing and acquisition, sampling and quantization; mathematical tools for DIP, intensity transformation, spatial filtering; discrete Fourier transform, filtering, image degradation, and restoration; noise models, estimating degradation function, image reconstruction; color models, color image processing, smoothing, sharpening; image segmentation, morphological image processing, image compression, pattern recognition.

Hours: XYZ where X = Lecture, Y = Lab, Z = Credit
All hours are per week.
3 Lab hours constitute 1 credit hour
1 credit hour implies 1 lecture of 50mins per academic week. 16 weeks in total.
Pre-Requisite courses are courses required to be completed before this course may be taken
Co-Requisite courses are courses required to be taken along with this course