a lossless compression scheme for bayer color filter

8/3/2019 A Lossless Compression Scheme for Bayer Color Filter

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A Lossless Compression Scheme for

Bayer Color Filter Array Images

King-Hong Chung and Yuk-Hee Chan,

IEEE Trans. On Image Procs., February,2008.


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Structure of the proposed

compression scheme

1. What is encoded(adaptive Rice Code encoding) for storage and

transmission is the residues, that is, the prediction errors.

2. Prediction: Green sub-image: intensity

Red/Blue sub-image: color difference signal (to remove

spectral redundancy)


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Prediction on the Green Plane(1)

candidates support region

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tes...candida)}1,1(),,2(),1,1(),2,({

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Green sub-image is raster scanned, then


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The matching extent of the support region of the candidates and the pixel of interest

is defined as follows: ( (m, n) is the position of one of the candidates)


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Rank the candidates by their matching extent to the pixel of interest:

(m1, n1) is the candidates with the maximum matching extent, and it

also defines the direction at pixel (i, j)

The pixel of interest is then predicted by

1.

2.Otherwise

The prediction error is then defined by


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Prediction on the Red/Blue Plane(1)


1. How color difference signals on the candidate pixels are determined would be

presented later.

2. Note that the matching extent is defined by the neighboring green pixels.


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Prediction on the Red/Blue Plane(1)


Color difference signal is then predicted by:

Note that region homogeneity classification is not used. This is because from the

experiments made by the authors, region homogeneity classification does not

improve the compression performance.


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Adaptive Color Difference Estimation(1)

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Adaptive Color Difference Estimation(2)

1.

2.


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Proposed Compression Scheme(1)

What is encoded is the residues, that is, the prediction errors.

Rice code is highly efficient in encoding exponentially distributed sources.

And all the values should be positive, so residues are remapped to

achieve this goal:

Each E(i, j) is split into a quotient and a remainder:

where k is a nonnegative integer. The quotient and remainder

are saved for storage and transmission.


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The length of the codeword used to represent E(i, j) is dependent on k, and is

given by:

For a geometric source S with distribution parameter

Optimal coding parameter k is given by:

,...2,1,0for)-(1)Prob( s !!! ssS VV

Here we need to know to determine optimal kV


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Expectation value of the source is given by

Here is estimated adaptively byQ

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initially.planesresidueallfor0set toiswhich,ofestimateprevioustheisandofestimatecurrenttheis

residueplanered/bluefor)}2,2(),,2(),2,2(),2,{(

residueplanegreenfor)}1,1(),,2(),1,1(),2,{(asdefinedis

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,

E

QQQQ

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jijijiji

jijijijiji


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Experimental Results(1)


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Experimental Results(2)

a lossless compression scheme for bayer color filter

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