This document discusses techniques for image coding and compression, including predicting pixel values from neighboring pixels, encoding differences between actual and predicted values (DPCM), and adapting the mapping of bits to differences over time (ADPCM). DPCM removes redundancy by transmitting only differences between samples, which are normally small. ADPCM varies this mapping dynamically so more bits can be used for rapid changes and fewer for slow changes. Overall the document focuses on prediction-based approaches to reduce image data by exploiting spatial and temporal correlations between pixels.
The pixel’s valuecan be predicted from its
neighbors’s value.
Sequences of pixels with similar value,
will be found along a row of the image
5.
To predict thevalue of a pixel from the
previous values of the same row
We predict that (for example)
We make an error doing the prediction!
If the actual value is (for example) the
error is
Information
transmitted
6.
Prediction
If we knowthe past behavior of a signal up to
a certain point in time, it is possible to make
some inference about its future values
Tapped-delay-line filter (discrete-time filter)
A simple and yet effective approach to implement the
prediction filter
With the basic delay set equal to the sampling period
Adaptive Differential PulseCode
Modulation (ADPCM)
Why we talk about ADPCM when we talk about DPCM ??
*Adaptive similar to DPCM, but vary the
mapping of bits to difference dynamically.
$ If rapid change, use large differences
$ If slow change, use small differences
12.
CS 414 -Spring 2012
Adaptive Differential Pulse Code
Modulation (ADPCM)
Fig : show the ADPCM
13.
Conclusion:
• DPCM canefficiently remove this
redundancy.
• Only the differences between
samples are sent.
• Normally the difference is small .
• The technology in which vary the
mapping of bits to difference
dynamically is ADPCM .