Image Processing (CACS404) is a 3-credit subject in BCA 7th Semester at Tribhuvan University. Below you'll find notes, old question papers, and lab reports aligned with the TU BCA curriculum.
Course Code: CACS404 | Credits: 3 | Semester: 7 | Curriculum: BCA Curriculum 2018
Digital image processing concepts, enhancement, and analysis.
This course presents an introduction to several topics on image processing techniques and their applications. It also explores the students’ real-world applications of image processing.
Upon completion of this course, students should be able to l. Explain the basic concepts of digital image processing and various image transforms. 2. Develop a broad range of image processing techniques and their applications. 3. To familiarize them with the image enhancement, image restoration and image segmentation techniques.
Image representation, basic relationship between pixels, elements of DIP system, elements of visual perception-simple image formation model, Sampling and Quantization, Color fundamentals and models, File Formats, Image operations. Brightness, contrast, hue, saturation, Mach band effect
Image Transforms, Fourier Transform and Discrete Fourier Transform, Fast Fourier Transform. Cosine Transform, Frequency domain image enhancement, low pass filtering, high pass filtering, homomorphic filter, Gaussian filter. – Spatial domain image enhancement, point processing, contrast stretching, clipping and thresholding, digital negative, intensity level slicing. Histogram processing: equalization, modification, Spatial filtering averaging, Smoothing and sharpening, median filtering, spatial low, high and band pass filters
Image Restoration – Image degradation model – Noise modeling – Blur, Inverse filtering- removal of blur caused by uniform linear motion, Wiener filtering, Morphological operation, erosion and dilation,
Need for compression, redundancy, pixel coding, run length coding, Hufknancoding, Elements of information theory, Error free compression, Lossy compression, Image compression standards- JPEG & MPEG, wavelet based image compression.
Laboratory work should be done covering all the topics listed above and a small project work should be carried out using the concept learnt in this course using software like matlab, python.