This document contains a question bank for a digital image processing course organized into 5 units. It includes questions about the basic concepts and components of digital image processing systems, image enhancement techniques like filtering and histogram processing, image compression standards and methods, color models, and image segmentation techniques like thresholding and edge detection. Some questions ask students to explain concepts in detail, while others involve calculations, examples, or distinguishing between different approaches. The document is intended to help students prepare to be tested on the key topics covered in a digital image processing course.
This presentation explains the Transform coding in easiest method possible. The graphics and diagrammatic representations are worth looking for. Simple language is another pro.
Image enhancement is the process of adjusting digital images so that the results are more suitable for display or further image analysis. For example, you can remove noise, sharpen, or brighten an image, making it easier to identify key features.
Here are some useful examples and methods of image enhancement:
Filtering with morphological operators, Histogram equalization, Noise removal using a Wiener filter, Linear contrast adjustment, Median filtering, Unsharp mask filtering, Contrast-limited adaptive histogram equalization (CLAHE). Decorrelation stretch
Histogram Processing
Histogram Equalization
Histogram Matching
Local Histogram processing
Using histogram statistics for image enhancement
Uses for Histogram Processing
Histogram Equalization
Histogram Matching
Local Histogram Processing
Basics of Spatial Filtering
This presentation explains the Transform coding in easiest method possible. The graphics and diagrammatic representations are worth looking for. Simple language is another pro.
Image enhancement is the process of adjusting digital images so that the results are more suitable for display or further image analysis. For example, you can remove noise, sharpen, or brighten an image, making it easier to identify key features.
Here are some useful examples and methods of image enhancement:
Filtering with morphological operators, Histogram equalization, Noise removal using a Wiener filter, Linear contrast adjustment, Median filtering, Unsharp mask filtering, Contrast-limited adaptive histogram equalization (CLAHE). Decorrelation stretch
Histogram Processing
Histogram Equalization
Histogram Matching
Local Histogram processing
Using histogram statistics for image enhancement
Uses for Histogram Processing
Histogram Equalization
Histogram Matching
Local Histogram Processing
Basics of Spatial Filtering
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Computer Graphics and Multimedia Techniques Paper (RTU VI Semester)FellowBuddy.com
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Modified Skip Line Encoding for Binary Image Compressionidescitation
Image Compression is an important issue in
Internet, mobile communication, digital library, digital
photography, multimedia, teleconferencing and other
applications. Application areas of Image Compression would
focus on the problem of optimizing storage space and
transmission bandwidth. In this paper, a modified form of skip
line encoding is proposed to further reduce the redundancy in
the image. The performance is found to be better than the
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research interest of protecting digital content
watermarking is extensively researched. In this paper
we present a novel watermark generation scheme
based on the histogram of the image and apply it to the
original image in the transform(DCT) domain. Further
we study the performance of the watermark against
some common attacks that can take place with images.
Experimental results show that the embedded
watermark is imperceptible and image quality is not
degraded.
The growing trend of online image sharing and downloads today mandate the need for better encoding and
decoding scheme. This paper looks into this issue of image coding. Multiple Description Coding is an
encoding and decoding scheme that is specially designed in providing more error resilience for data
transmission. The main issue of Multiple Description Coding is the lossy transmission channels. This work
attempts to address the issue of re-constructing high quality image with the use of just one descriptor
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quantizer. We propose and compare 4 coders by examining the quality of re-constructed images. The 4
coders are namely JPEG HH (Horizontal Pixel Interleaving with Huffman Coding) model, JPEG HA
(Horizontal Pixel Interleaving with Arithmetic Encoding) model, JPEG VH (Vertical Pixel Interleaving
with Huffman Encoding) model, and JPEG VA (Vertical Pixel Interleaving with Arithmetic Encoding)
model. The findings suggest that the use of horizontal and vertical pixel interleavings do not affect the
results much. Whereas the choice of quantizer greatly affect its performance.
nternational Journal of Computational Engineering Research(IJCER)ijceronline
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SECURED COLOR IMAGE WATERMARKING TECHNIQUE IN DWT-DCT DOMAIN ijcseit
The multilayer secured DWT-DCT and YIQ color space based image watermarking technique with
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noise ratio and Normalized correlations are used as measurement metrics. The 512x512 sized color images
with different histograms are used for testing and watermark of size 64x64 is embedded in HL region of
DWT and 4x4 DCT is used. ‘Haar’ wavelet is used for decomposition and direct flexing factor is used. We
got PSNR value is 63.9988 for flexing factor k=1 for Lena image and the maximum NC 0.9781 for flexing
factor k=4 in Q color space. The comparative performance in Y, I and Q color space is presented. The
technique is robust for different attacks like scaling, compression, rotation etc.
In this paper, we describe an FPGA H.264/AVC encoder architecture performing at real-time. To reduce the critical path length and to increase throughput, the encoder uses a parallel and pipeline architecture and all modules have been optimized with respect the area cost. Our design is described in VHDL and synthesized to Altera Stratix III FPGA. The throughput of the FPGA architecture reaches a processing rate higher than 177 million of pixels per second at 130 MHz, permitting its use in H.264/AVC standard directed to HDTV.
A novel approach to Image Fusion using combination of Wavelet Transform and C...IJSRD
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1. SSGBCOE&T, Bhusawal Electronics & Communication Department
Digital Image Processing Question Bank
UNIT -I
1) Describe in detail the elements of digital image processing system. & write note on
Sampling and Quantization?
2) Write the Hadamard transform matrix Hn for n=3?
3) Mention the significant features of wavelet transform?
4) Discuss the salient features of Discrete Cosine transform?
5) What is meant by the Histogram of a digital image?
6) Write a note on Image sensing and Acquisition?
7) Explain about fundamental steps in digital image processing?
8) Explain the components of an Image Processing system?
9) a) Distinguish between digital image, and binary image. Give suitable example to each type
of images.
b) State and explain various applications of digital image processing
10) a) Explain the functioning of CCD line scan sensor and CCD area sensor.
b) What is a frame buffer? Discuss the categories of digital storage for image
processing applications.
11) Write Short Note on these various transforms:
a) Walsh
b) Hadamard
c) Wavelet
12) What is m-connectivity among pixels? Give an example
13) What do you mean sampling? State Explain this into image processing?
14) What are the different transforms used in DIP? Explain the most advantageous one detail ?
15) Explain resolution with image processing .Also write on spatial level resolution?
16) What are the different elements of DIP system .Explain?
17) Explain with example a) Neighbors of pixel b) Connectivity
18) How many minutes would it take to transmit a 1024 * 1024 image with 256 gray levels using
a 56k band modem? Explain it .
Prepared By: Mr.Nilesh George Nirmal, Electronics & Communication Department, SSGBCOE&T, Bhusawal 1
2. SSGBCOE&T, Bhusawal Electronics & Communication Department
UNIT II
1. Discuss Image smoothing with the following
(a) Low pass spatial filtering (b) Median filtering.
2. Discuss in detail about Histogram Processing?
3. Write a note on basics of spatial filtering?
4. Write a note on
a) Gray Level Transformations
b) Combining Spatial Enhancement Methods
5. Distinguish between spatial domain techniques and frequency domain techniques of Image
enhancement
6. State and explain with suitable examples the arithmetic/logic operations among Pixels.
7. (a) Explain about Histogram specification with necessary derivations
(b) What is meant by local enhancement? Discuss its importance.
8. (a) Show that a high pass-filtered image in the frequency domain can be obtained
by using the method of subtracting a low pass filtered image from the original.
9. (a) What is meant by image enhancement? Discuss the need for enhancement
(b) Discuss the spatial domain methods for image enhancement.
10. (a) Show that a high pass-filtered image in the frequency domain can be obtained
by using the method of subtracting a low pass filtered image from the original.
11. Describe the concept of Histogram specifications and Histogram modification for image
enhancement & discuss the role of nonlinear filters in image enhancement.
12. Explain process of image smoothing using Median filtering?
13. How first and second derivative enhance the image ? Explain which is more enhance?
14.An image segment is show below .let V be the set of gray level values used to define
connectivity in the image .Compute D4 ,D8 and Dm distances between pixel p & q for
a) v = { 0,1} b) v = {1,2}
15. Develop a procedure for computing the median of an n*n neighborhood .Propose a technique
for updating the median as the center of the neighborhood is moved from pixel to pixel
16. Under what conditions does the butterworth low pass filter H(u,v)=1/1+ [D(u,v)/Do]2n
becomes an ideal low pass filter ? Explain
17. Explain the discrete histogram equalization technique?
Prepared By: Mr.Nilesh George Nirmal, Electronics & Communication Department, SSGBCOE&T, Bhusawal 2
3. SSGBCOE&T, Bhusawal Electronics & Communication Department
UNIT III
1. Discuss the salient features of Discrete Cosine transform?
2. Explain Huffman coding with an example and mention its salient features.& Describe the
lossless predictive coding of images.
3. Discuss the image restoration process in linear algebraic approach.
4. (a) Draw and explain a general compression system model.
(b) Draw the relevant diagram for source encoder and source decoder.
5. Explain the Image compression models.
6. Discuss on Error Free compression
7. Describe the various noise models
8. Explain the Image compression standards
9. (a) Discuss the functioning of source encoder and decoder in image Compression.
(b) Explain about Huffman coding with suitable examples.
10. What are the different coding techniques used in DIP ? Explain any one
11. Explain Lossy Predictive coding Model?
12. Explain any image compression process in detail?
13. Determine which bit, if any, is in error in the hamming encoded message 1100111,
1100110 and 1100010.what are the decoded values?
Prepared By: Mr.Nilesh George Nirmal, Electronics & Communication Department, SSGBCOE&T, Bhusawal 3
4. SSGBCOE&T, Bhusawal Electronics & Communication Department
UNIT IV
1.Explain about the CMY and CMYK color models in detail?
2.What is invariant degradation? Explain about estimating the degradation function?
3.Write a note on Geometric mean Filter.
4.Write a note on
a)Gray Level Transformations b)Spatial Enhancement Methods
5.Write about how the colors are converted from RBG to HIS
6. (a) Explain about RGB and CMY color models.
(b) Discuss the procedure for conversion from HSI to RGB color model.
7.(a) Explain the image degradation model for continuous functions
(b) Discuss about unconstrained, constrained restorations.
8.Draw the block diagram of Image restoration system & explain each block critically?
9.Explain the following Color models
a) RGB b) CMY c)HSI d) HIS
10. Explain the principle of pseudo color image processing
11. What are the different mean filters used for restoration? Explain any one.
12. Write note on a) RGB b) HIS
13. Explain the color conversion with appropriate method in detail.
14. Explain the spatial transformation in DIP
15. Write in detail gray level interpolation based on the nearest neighbor concept.
Prepared By: Mr.Nilesh George Nirmal, Electronics & Communication Department, SSGBCOE&T, Bhusawal 4
5. SSGBCOE&T, Bhusawal Electronics & Communication Department
UNIT V
1. Explain the significance of Hough Transform .List the advantages over other
transforms?
2. Explain the use of motion in segmentation?
3. Write about various edge Detectors available in function edge?
4. Explain any type of transform for the detection of line and curves?
5. Explain briefly
a) Region based segmentation
b) Use of Motion in segmentation
6. What is Thresholding? Explain about Global Thresholding.
7. Explain in detail the interactive restoration of an image.
8. Discuss about Global processing via the Hough Transform.
9. Discuss about unconstrained, constrained restorations.
10. Explain in detail the threshold selection based on boundary characteristics.
11. Discuss about Region growing by pixel aggregation.
12. Discuss about unconstrained, constrained restorations.
13. What is meant by image segmentations? Discuss various applications of it.
14. What is meant by discontinuities in an image? Discuss about point detection,
line detection ?
15. Explain global processing using Hough transform.
16. What are the different techniques for detection of discontinuous? Explain advantageous
one only.
17. Write note on image segmentation in detail.
18. What are the gradient operation? What are the various operators used for image
segmentation based on edge detection? Explain
19. What do you understand by dialation and erosion operation in morphological
operation? Explain in brief?
Prepared By: Mr.Nilesh George Nirmal, Electronics & Communication Department, SSGBCOE&T, Bhusawal 5
![SSGBCOE&T, Bhusawal Electronics & Communication Department
UNIT II
1. Discuss Image smoothing with the following
(a) Low pass spatial filtering (b) Median filtering.
2. Discuss in detail about Histogram Processing?
3. Write a note on basics of spatial filtering?
4. Write a note on
a) Gray Level Transformations
b) Combining Spatial Enhancement Methods
5. Distinguish between spatial domain techniques and frequency domain techniques of Image
enhancement
6. State and explain with suitable examples the arithmetic/logic operations among Pixels.
7. (a) Explain about Histogram specification with necessary derivations
(b) What is meant by local enhancement? Discuss its importance.
8. (a) Show that a high pass-filtered image in the frequency domain can be obtained
by using the method of subtracting a low pass filtered image from the original.
9. (a) What is meant by image enhancement? Discuss the need for enhancement
(b) Discuss the spatial domain methods for image enhancement.
10. (a) Show that a high pass-filtered image in the frequency domain can be obtained
by using the method of subtracting a low pass filtered image from the original.
11. Describe the concept of Histogram specifications and Histogram modification for image
enhancement & discuss the role of nonlinear filters in image enhancement.
12. Explain process of image smoothing using Median filtering?
13. How first and second derivative enhance the image ? Explain which is more enhance?
14.An image segment is show below .let V be the set of gray level values used to define
connectivity in the image .Compute D4 ,D8 and Dm distances between pixel p & q for
a) v = { 0,1} b) v = {1,2}
15. Develop a procedure for computing the median of an n*n neighborhood .Propose a technique
for updating the median as the center of the neighborhood is moved from pixel to pixel
16. Under what conditions does the butterworth low pass filter H(u,v)=1/1+ [D(u,v)/Do]2n
becomes an ideal low pass filter ? Explain
17. Explain the discrete histogram equalization technique?
Prepared By: Mr.Nilesh George Nirmal, Electronics & Communication Department, SSGBCOE&T, Bhusawal 2](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)