Assignment $1$: Digital Image Processing with Spatial and Frequency Enhancements

Overview:

This assignment is designed to explore and apply spatial and frequency domain enhancements on a

dataset of their choice.

Programming language: Python.

Objectives:

$1.$ To understand and implement spatial domain image processing techniques.

$2.$ To understand and apply frequency domain image processing methods.

$3.$ To analyze the effectiveness of different enhancement techniques on various datasets.

Assignment Tasks:

$1.$ Dataset Selection $($any image dataset$)$:

$-$ Select a dataset consisting of at least $10$ images. The dataset can be chosen based on

the student's interest, such as medical images, natural scenes, or artificial objects.

Justify the selection with a brief description.

$2.$ Spatial Domain Enhancement $(2$ marks$)$:

$-$Implement at least two spatial domain enhancement techniques $($e$.$g$.,$ histogram

equalization, spatial filtering$).$

$-$Apply these techniques to your selected dataset.

$-$Document the process and results, including before$-$and$-$after comparisons for each

image.

$3.$ Frequency Domain Enhancement $(2$ marks$)$:

$-$Implement at least two frequency domain enhancement methods $($e$.$g$.,$ Fourier

Transform for filtering, frequency domain smoothing$/$sharpening$).$

$-$Apply these methods to the same dataset.

$-$Document the process and results, with comparative analysis similar to the spatial

domain section.

$4.$ Analysis and Conclusion $(0\mathrm{.}5$ marks$)$:

$-$Analyze the effectiveness of the applied techniques on your dataset. Discuss the

differences in the results between spatial and frequency domain enhancements.

$-$Conclude which method$($s$)$ worked best for your dataset and why.