Data compression unit 5 mcq
1. Characteristic of a vector quantizer
(A) Multiple quantization indexes are represented by one codeword
(B) Each input symbol is represented by a fixed-length codeword
(C) Multiple input symbols are represented by one quantization index
(D) All of the above
2. Vector quantization is rarely used in practical applications, why?
(A) The coding efficiency is the same as for scalar quantization
(B) The computational complexity, in particular for the encoding, is
much higher than in scalar quantization and a large codebook needs to be
stored
(C) It requires block Huffman coding of quantization indexes, which is very complex
(D) All of the above
3. Let N represent the dimension of a vector quantizer. What statement about the performance of the best vector quantizer with dimension N is correct?
(A) For N approaching infinity, the quantizer performance asymptotically
approaches the rate-distortion function (theoretical limit)
(B) By doubling the dimension N, the bit rate for the same distortion is halved
(C) The vector quantizer performance is independent of N
(D) All of the above
4. Which of the following is/are correct for advantage of vector quantization over scalar quantization
(A) Vector Quantization can lower the average distortion with the number of reconstruction levels held constant
(B) Vector Quantization can reduce the number of reconstruction levels when distortion is held constant
(C) Vector Quantization is also more effective than Scalar Quantization When the source output values are not correlated
(D) All of the above
5. Vector quantization is used for
(A) Lossy data compression
(B) Lossy data correction
(C) Pattern recognition
(D) All of the above
6. The Linde–Buzo–Gray algorithm is a ______ quantization algorithm to derive a good codebook.
(A) Scalar
(B) Vector
(C) Both
(D) None of the above
7. Vector quantization is used in
(A) Video coding
(B) Audio coding
(C) Speech coding
(D) All of the above
8. What are process(Techniques) used in video coding?
(A) Partition of frames into macro blocks
(B) Form of Vector Quantization
(C) Both (A) & (B)
(D) None of these