Answer Key for DIP

Mar 2010 Question Papers

Question 1 A

• Explain the working principle of Laser printing device.

Question 1 B(1+3+1+3+2) Marks

• What is the difference between image sampling and image quantization? Why is it so important?

Image Sampling andQuantization

Question 2A (4+4+2)

• What is Discrete Cosine Transform? How is it different from Discrete Fourier Transform? What are its applications?

DCT - Introduction

• The discrete cosine transform (DCT) is a technique for converting a signal into elementary frequency components. It is widely used in image compression

• All three of the following standards employ a basic technique known as the discrete cosine transform (DCT). Developed by Ahmed, Natarajan, and Rao [1974], the DCT is a close relative of the discrete Fourier transform (DFT).– JPEG – For compression of still images– MPEG – For compression of motion video– H.261 - For compression of video telephony and

teleconferencing

DCT• Each image is subdivided into 8x8 blocks and 2

D DCT is applied to each block image f( i,j), with output being the DCT co-efficients F (u,v) for each block.

The DCT Matrix

Doing the DCT on 8*8 block

Performing DCT (Final Step)

DCT versus DFT

• The DFT transformation kernel is linear, separable and symmetric. Hence, like DCT, it has fixed basis images and fast implementations are possible.

• It also exhibits good decorrelation and energy compaction characteristics. However, the DFT is a complex transform and therefore stipulates that both image magnitude and phase information be encoded.

• In addition, studies have shown that DCT provides better energy compaction than DFT for most natural images.

• Furthermore, the implicit periodicity of DFT gives rise to boundary discontinuities that result in significant high-frequency content.

Properties of DCT

• Properties of the DCT which are of particular value to image processing applications.

• Decorrelation– Uncorrelated transform coefficients which can be encoded

independently.

• Energy Compaction – DCT exhibits excellent energy compaction for highly correlated images.

• Separability– The DCT transform equation can be computed in two steps by

successive 1-D operations on row and column of images

• Symmetry– Provides orders of magnitude improvement in computation efficiency

Question 2B

• What is the difference between point processing and neighborhood processing? Explain smoothening operations.

Question 3 A

• What is contrast stretching? Explain different contrast stretching operations. (2+4+4)

Contrast Stretching

• One of the simplest piecewise linear functions is a contrast-stretching transformation.

• Low-contrast images can result from poor illumination, lack of dynamic range in the imaging sensor, or even the wrong setting of a lens aperture during image acquisition. Contrast stretching is a process that expands the range of intensity levels in an image so that it spans the full intensity range of the recording medium or display device.

piecewise linear functions