Exploring Image Processing Concepts

What is the difference between continuous and discrete images?

• Continuous images are pixelated and blocky, while discrete images are smooth and fluid.

• Continuous images are made of pixels, while discrete images are made of vectors.

• Continuous images can only be displayed in black and white, while discrete images can be in color.

• Continuous images are smooth and fluid, while discrete images consist of distinct, separate values.

Define luminance and its role in image processing.

• Luminance is the speed at which an image is processed by a computer.

• Luminance refers to the color saturation in an image.

• Luminance is the intensity of light in an image, crucial for brightness and detail representation in image processing.

• Luminance is the measurement of sound intensity in audio processing.

Explain the concept of aliasing in 2-D sampling theory.

• Aliasing refers to the enhancement of high-frequency components in a signal.

• Aliasing is the distortion that occurs when a signal is undersampled, causing high-frequency components to be misrepresented as lower frequencies.

• Aliasing is the process of increasing the sampling rate of a signal.

• Aliasing occurs when a signal is perfectly sampled without any distortion.

What is the purpose of image quantization?

• The purpose of image quantization is to reduce the number of colors in an image for compression and processing efficiency.

• To enhance the resolution of an image.

• To increase the number of colors in an image.

• To apply filters for artistic effects.

Describe the Lloyd Max Quantizer and its application.

• The Lloyd Max Quantizer is primarily used for image enhancement.

• The Lloyd Max Quantizer is designed for real-time video streaming applications.

• The Lloyd Max Quantizer is a type of audio filter for noise reduction.

• The Lloyd Max Quantizer is used in signal processing and data compression to optimally quantize continuous signals into discrete levels.

What are the characteristics of linear systems in image processing?

• Superposition and homogeneity

• Invariance and discontinuity

• Non-linearity and randomness

• Additivity and linearity

List the types of 2-D orthogonal transforms used in image processing.

• Radial Basis Function (RBF)

• Principal Component Analysis (PCA)

• Support Vector Machine (SVM)

• Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Discrete Wavelet Transform (DWT)

What is the significance of histogram equalization in image enhancement?

• Histogram equalization eliminates noise from images entirely.

• Histogram equalization changes the color of the image to grayscale.

• Histogram equalization improves image contrast and visibility by redistributing pixel intensity values.

• Histogram equalization reduces image size by compressing pixel data.

Explain the difference between low pass and high pass filtering.

• Low pass filters allow low frequencies to pass and attenuate high frequencies; high pass filters allow high frequencies to pass and attenuate low frequencies.

• Low pass filters block all frequencies; high pass filters allow all frequencies.

• Low pass filters amplify high frequencies; high pass filters amplify low frequencies.

• Low pass filters are used for digital signals; high pass filters are used for analog signals.

What techniques are used for edge enhancement in images?

• Color inversion

• Sobel filter, Laplacian filter, unsharp masking

• Gaussian blur

• Histogram equalization