WorksheetsUnit II Quiz Image Processing Techniques
Total questions: 10
Worksheet time: 5mins
Which of the following is an example of an orthogonal transform?
Hadamard Transform
Haar Transform
Karhunen–Loève Transform
All of the above
The Karhunen–Loève (KL) Transform is also known as:
Principal Component Analysis (PCA)
Fast Fourier Transform (FFT)
Discrete Cosine Transform (DCT)
Walsh Transform
The Fourier Transform converts an image from:
Time domain to Space domain
Spatial domain to Frequency domain
Frequency domain to Spatial domain
Both b and c
The Haar Transform is mainly useful because:
It is complex and computationally expensive
It provides localized information in both time and frequency
It is only used in audio signals
It is not invertible
The Hadamard Transform uses only:
Real numbers (+1 and –1)
Complex exponential functions
Sinusoidal functions
Wavelet filters
In Histogram Equalization, the main purpose is:
Smoothing of the image
Improving the contrast of the image
Noise reduction
Data compression
Image smoothing in the spatial domain is typically achieved by:
High-pass filtering
Low-pass filtering
Edge detection
Histogram equalization
Sharpening filters in the frequency domain correspond to:
Low-pass filters
Band-pass filters
High-pass filters
Notch filters
In image enhancement, Laplacian filter is mainly used for:
Smoothing
Edge enhancement (sharpening)
Contrast adjustment
Noise reduction
The Fourier Transform is best suited for analyzing:
Localized time variations
Frequency content of stationary signals
Energy compaction in images
Piecewise constant signals
