Data Compression MCQ Online Test | Practice Set-5 by TodayQuiz Welcome to your Data Compression MCQ Online Test | Practice Set-5 Click on next Button to Continue the Quiz... 1. he sequence of operations in which PCM is done is Quantizing, sampling, encoding None of the above Quantizing, encoding, sampling Sampling, quantizing, encoding 2. Vector quantization is used in Video coding Speech coding All of the above Audio coding 3. Transform coding, vector quantization are examples for______ Lossy compression Transmission Pixel compression 4. Gzip (short for GNU zip) generates compressed files that have a _ ____extension. .gzp .gz .g .gzip 5. Shannons theorem is also called noiseless coding theorem noiseless coding theorem coding theorem noiseless theorem 6. The process of converting the analog sample into discrete form is called Modulation Multiplexing Sampling Quantization 7. Vector quantization is rarely used in practical applications, why? The coding efficiency is the same as for scalar quantization All of the above The computational complexity, in particular for the encoding, is much higher than in scalar quantization and a large codebook needs to be stored It requires block Huffman coding of quantization indexes, which is very complex 8. Let N represent the dimension of a vector quantizer. What statement about the performance of the best vector quantizer with dimension N is correct? All of the above By doubling the dimension N, the bit rate for the same distortion is halved The vector quantizer performance is independent of N For N approaching infinity, the quantizer performance asymptotically approaches the rate distortion function (theoretical limit) 9. Compression Technique used in Audio is Differential Encoding Entropy Coding Transformation Encoding Differential & Transformation Encoding 10. Which model is known as ignorance model? Markov model Probability model Physical model Composite Source Model 11. For a continuous image f(x, y), Quantization is defined as All of the mentioned None of the mentioned Digitizing the coordinate values Digitizing the amplitude values 12. The probability density function of the envelope of narrow band noise is Rician Rayleigh Uniform Gaussian 13. Expansion of LZW Coding is Lempel-ziv Lossless Lempel-ziv-welsh Lossy 14. Compression Technique used in Image Video is Huffman Coding Differential Encoding Transformation Coding Entropy Coding 15. ______ is normally used for the data generated by scanning the documents, fax machine, typewriters etc Transformation Coding Vector Quantization Runlength Encoding Huffman Coding 16. Characteristic of a vector quantizer Each input symbol is represented by a fixed-length codeword Multiple input symbols are represented by one quantization index Multiple quantization indexes are represented by one codeword All of the above 17. To convert a continuous sensed data into Digital form, which of the following is required? Quantization Neither Sampling nor Quantization Sampling Both Sampling and Quantization 18. The Linde–Buzo–Gray algorithm is a ______ quantization algorithm to derive a good codebook. Both Scalar None of the above Vector 19. Which of the following is the slowest compression technique? Gzip All of the mentioned LZO Bzip2 20. Entropy Coding is an ________ Both Lossless None Lossy 21. What are process(Techniques) used in video coding? A. Partition of frames into macro blocks D. None of these C. Both (A) & (B) B. Form of Vector Quantization 22. Which conveys more information? Low probability event High probability event None of the mentioned High & Low probability event 23. By what name(s) the element of this matrix array is called None of the mentioned All of the mentioned Image element or Picture element Pixel or Pel 24. Expansion of LZ Coding is Lempel-ziv-welsh Lempel-ziv Lossy Lossless 25. Which of the following is/are correct for advantage of vector quantization over scalar quantization Vector Quantization can reduce the number of reconstruction levels when distortion is held constant Vector Quantization is also more effective than Scalar Quantization When the source output values are not correlated Vector Quantization can lower the average distortion with the number of reconstruction levels held constant All of the above 26. Vector quantization is used for Pattern recognition All of the above Lossy data compression Lossy data correction
