MIT6_003S10_lec23_handout

MIT6_003S10_lec23_handout - 6.003: Signals and Systems...

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6.003: Signals and Systems Lecture 23 May 4, 2010 6.003: Signals and Systems Quantization and Modulation Last Time Quantization: discrete representation of amplitudes. -1 -1 0 0 1 1 Input voltage Output voltage 2 bits 3 bits 4 bits 00 01 10 0 0.5 1 -1 0 1 Time (second) 0 0.5 1 Time (second) 0 0.5 1 Time (second) -1 0 1 Input voltage -1 0 1 Input voltage Digital representations of signals require discrete representations of both the independent variable (time, space, ...) and dependent variable (amplitude). May 4, 2010 Quantizing Images Quantizing creates distortion. 8 bits 6 bits 4 bits 3 bits 2 bits 1 bit Quantization Adding noise (dither) can reduce the perceptual effect of quantiza- tion. Quantization: y = Q ( x ) Quantization with dither: y = Q ( x + n ) Quantizing Images Adding noise (dither) reduces “banding” in images. 3 bits 2 bits 1 bit 3 bits dither 2 bits dither 1 bit dither Quantizing Sound Adding noise (dither) can reduces “distortions” in sound. 16 bits/sample 4 bits/sample 4 bits with dither/sample 3 bits/sample 3 bits with dither/sample 2 bit/sample 2 bit with dither/sample J.S. Bach, Sonata No. 1 in G minor Mvmt. IV. Presto Nathan Milstein, violin 1
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6.003: Signals and Systems Lecture 23 May 4, 2010 Robert’s Technique Robert’s technique decorrelates quantization errors from the signal. Quantization: y = Q ( x ) Quantizing Images Robert’s technique decorrelates quantization errors from the signal. Quantization with dither: y = Q ( x + n ) Quantization with Robert’s technique: y = Q ( x + n ) n Quantizing Sound Robert’s technique decorrelates quantization errors from the signal. 16
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MIT6_003S10_lec23_handout - 6.003: Signals and Systems...

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