Analyse the key stages in Digital Image Processing.

Analyse the connectivity and adjacency of pixels using suitable equations.

Describe the importance of Digital Image Processing.

What is digital image and what is digital image processing? Explain shortly.

What do you mean by Image and Digital Image processing?

Describe all the key stages of digital image processing.

Differentiate between Analog and digital image processing.

Describe briefly down fundamental steps of Digital image processing.

Why need spatial filtering in DIP? List down the various spatial filtering techniques of DIP.

Most frequently used DIP application areas shortly elucidate.

What is Histogram processing? Mention various application of Histogram Processing?

Describe the image sampling and quantisation with suitable figures and equations.

Distinguish between spatial and intensity level resolution.

Distinguish between the intensity level: i) Logarithmic, ii) Power law.

Analyse the connectivity and adjacency of pixels using suitable equations.

Analyse the connectivity and adjacency of pixels using suitable equations.

Describe the image sampling and quantisation with suitable figures and equations.

Explain the concept of histogram equalization. How does it improve the contrast of an image?

Explain an image restoration process with a suitable diagram and equations.

Explain the region-based segmentation technique. How does it differ from edge-based segmentation?

Describe some applications of lossy and lossless image compression techniques.

What is color model? Describe in brief about RGB, CMYK and HSI color models.

There are different filters commonly used for removing noise from an image. Briefly describe two of them.

What is object recognition? Describe the major components of object recognition.

What do you mean by Digital Image processing (DIP)?

Describe basic relationships between pixels using Neighborhood (N4, Ns), Adjacency, Connectivity and paths.

What is color model? Describe in brief RGB, CMYK and HIS color models.

Perform Histogram Equalization on Gray level distribution shown in the table. Draw the histograms of the original and equalized images. Comment on the contrast of the image before histogram equation and after histogram equalization.

What are the necessity image smoothing and image sharpening in DIP?

Why need structuring element in morphological image processing?

What do you mean by Image and Digital Image processing?

Describe basic relationships between pixels using Neighborhood (N4, N8), Adjacency, Connectivity and paths with examples.

What is image filtering? Why its necessity is very crucial in DIP?

What is the Histogram Processing in DIP? Mention various advantages/disadvantages of Histogram Processing?

What is the noise of image? Mention the variations of image noise? How to solve them?

What is Pattern Recognition? Why do you feel the uses of Pattern Recognition in DIP?

Why need structuring element in morphological image processing?

Describe Thinning and Thickening operation elaborately.

Describe basic relationships between pixels using Neighborhood, Adjacency, Connectivity, paths, Region, and Boundary.

What is the image smoothing and image sharpening filter? Shows first order derivative and second order derivative filtering for image sharpening.

Perform histogram equalization on gray level distribution shown in the following table. Draw the histograms of the original and equalized images.

Explain image degradation in the context of digital image processing. What can cause to degrade an image?

How K-means clustering method is used in image segmentation. Explain its main steps with a proper example.

What is Huffman coding in the context of digital image processing. Suppose we have a 5×5 raster image with 8-bit color, i.e. 256 different colors. So, the uncompressed image will take 5 x 5 x 8 =200 bits of storage. Now do the Huffman coding for the following distribution of the colors and find out the compression ratio of that image. There are only 4 unique colors: white, black, red and blue. White 14 times, Black 6 times, Red 3 times, Blue 2 times

What are boundary descriptors and regional descriptors in image description. Describe them briefly.

How does the morphological operation of dilation work? Explain its effects on binary images.

Discuss the role of feature extraction in image recognition. Provide examples of commonly used features.

"DIP has diverse application areas in our modern life". Give your opinions regarding this fact.

Explain in short sampling and quantization method for digital image?

Explain color model conversion using mathematical calculation from RGB to HSI and HSI to RGB.

Shortly mention the relation between intensity transformation and spatial filtering. Discuss any two intensity transformation function among Linear transform, Log transform, Power law transform for an eight bit image.

Shows first order derivative and Laplacian filtering for DIP.

Explicate morphological image processing fundamental operation Dilation and Erosion with suitable diagram.

Explain model of image degradation/restoration process with a block diagram.

Explain the concept of thresholding in image segmentation and write its merits and demerits.

Describe briefly fundamental steps of Digital image processing with a suitable diagram.

Explain image formation procedure on Human Eye and Digital Camera.

Write short notes on Blurring and Noise Reduction Filter.

Perform Histogram Equalization on Gray level distribution shown in the table. Draw the histograms of the original and equalized images. Comment on the contrast of the image before histogram equation and after histogram equalization.

What is color model? Describe in brief RGB, CMYK and HIS color models.

What is Image Segmentation? Is it essential in DIP?

Explicate morphological image processing fundamental operation Dilation and Erosion with suitable diagram.

Write short note on: i) Huffman Coding ii) Run-length encoding iii) Prewitt Operator

Short notes on Intensity transformation function for an eight bit image (i) Linear transform (ii) Log transform (iii) Power law transform for an eight bit image.

What is image acquisition? Briefly describe the process of image acquisition.

Describe shortly about the major components of digital image processing.

Compare and contrast spatial domain and frequency domain techniques for image enhancement. Provide examples.

Write shortly about the Gaussian noise and Impulse noise in the context of digital image processing.

Discuss the challenges in thresholding for image segmentation. Provide examples of adaptive thresholding methods.

What is the difference between luminance and chrominance?

What are the basic mathematical tools used in digital image processing? Explain, how can Fourier transform help in digital image processing?

Describe some evaluation metrics which are commonly used in object recognition.

Draw the sequence of fundamental steps of Digital image processing. Also elaborately explain.

Describe components of a general purpose image processing system.

What is image acquisition? Briefly describe the process of image acquisition.

What is Histogram processing? Mention various application of Histogram Processing?

Make a comparative analysis of opening and closing operation in morphological processing.

Briefly describe the Canny edge detection technique for image segmentation.

What are the major components of Digital Image Processing?

What are the necessity image smoothing and image sharpening in DIP?

Discuss any two-intensity transformation function among Linear transform, Log transform, Power law transform for an eight-bit image.

Explain color model conversion using mathematical calculation from RGB to HSI and HSI to RGB.

Write down basic characteristics of Image Segmentation types and techniques.

Make a comparative analysis of opening and closing operation in morphological processing.

What is noise in image? Describe frequently known image noises.

Write short note on the Prewitt and Sobel operator.

Shows first order derivative and Laplacian filtering for DIP.