Image Processing Introduction

IC 040 IMAGE PROCESSING

This is my elective of my fifth Semester, I had to choose between Image Processing, Power Electronics, and Digital Signal Processing.

I had pegged P.E to be a really theoretical subject with definitions etc, but it turns out they have got a really awesome temp faculty who uses graphs to talk in detail about the subject.

In I.P (Image processing - an acronym I will be using from now on)
I plan to use code samples to illustrate all points that I learn, for this I will be using MATLAB, and python libraries such as PIL, numpy, mathplotlib, scipy etc. I recommend getting a mathematical package like Python(x,y) rather than installing these packages separately on your python installation.

These are my portions, and just as no subject is boring, I don’t think any subject for any course in my college has a seriously out of date syllabus. So here goes :-

Linearity and space-invariance, PSF, Discrete images and image transforms, 2-D sampling and reconstruction, Image quantization, 2-D transforms and properties.

Image enhancement - Histogram modelling, equalization and modification. Image smoothing , Image crispening. Spatial filtering, Replication and zooming, Generalized cepstrum and homomorphic filtering.

Image restoration - image observation models. Inverse and Wiener filtering. Filtering using image transforms. Constrained least-squares restoration. Generalized inverse, SVD and interactive methods. Recursive filtering.Maximum entropy restoration. Bayesian methods.

Image data compression - sub sampling, Coarse quantization and frame repetition. Pixel coding - PCM, entropy coding, runlength coding Bit-plane coding. Predictive coding. Transform coding of images. Hybrid coding and vector DPCM. Interframe hybrid coding.

Image analysis - applications, Spatial and transform features. Edge detection, boundary extraction, AR models and region representation. Moments as features. Image structure. Morphological operations and transforms. Texture Scene matching and detection. Segmentation and classification.

Yeah so when I saw the portions it looked really daunting to me too!
But here goes,

Imaging Systems and their relationship with Point Spread Function

Discrete images and image transforms

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