synwtfilterintlift5x3.java

jpeg2000编解码

                        int[] highSig, int highOff, int highLen, int highStep, 
                        int[] outSig, int outOff, int outStep) {
                        
        int i;
        int outLen = lowLen + highLen; //Length of the output signal
        int iStep = 2*outStep; //Upsampling in outSig
        int ik; //Indexing outSig
        int lk; //Indexing lowSig
        int hk; //Indexing highSig
        
        /* Generate even samples (inverse low-pass filter) */
        
        //Initialize counters
        lk = lowOff;
        hk = highOff;
        ik = outOff + outStep;
 
        //Apply lifting step to each "inner" sample.
        for(i = 1; i<outLen-1; i += 2) {
            outSig[ik] = lowSig[lk] - 
                ((highSig[hk] + highSig[hk+highStep] + 2)>>2);
            
            lk += lowStep;  
            hk += highStep;
            ik += iStep;
        }
        
        if ( (outLen>1) && (outLen%2==0) ) {
            // symmetric extension.
            outSig[ik] = lowSig[lk] - ((2*highSig[hk]+2)>>2);
        }
        /* Generate odd samples (inverse high pass-filter) */
         
        //Initialize counters
        hk = highOff;
        ik = outOff;
        
        if ( outLen>1 ) {
            outSig[ik] = highSig[hk] + outSig[ik+outStep];
        }
        else {
	    // Normalize for Nyquist gain
            outSig[ik] = highSig[hk]>>1;
        }
        
        hk += highStep;
        ik += iStep; 
        
        //Apply first lifting step to each "inner" sample.
        for(i = 2; i < outLen-1; i += 2) {  
            // Since signs are inversed (add instead of substract)
            // the +1 rounding dissapears.
            outSig[ik] = highSig[hk] + 
                ((outSig[ik-outStep] + outSig[ik+outStep]) >> 1);
            hk += highStep;
            ik += iStep;   
        }

        //Handle head boundary effect if input signal has odd length.
        if(outLen%2==1 && outLen>1) {
            outSig[ik] = highSig[hk] + outSig[ik-outStep];
        }
    }
    
    /**
     * Returns the negative support of the low-pass analysis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * @return 2
     * */
    public int getAnLowNegSupport() {
        return 2;
    }

    /**
     * Returns the positive support of the low-pass analysis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * @return The number of taps of the low-pass analysis filter in the
     * positive direction
     * */
    public int getAnLowPosSupport() {
        return 2;
    }

    /**
     * Returns the negative support of the high-pass analysis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * @return The number of taps of the high-pass analysis filter in the
     * negative direction
     * */
    public int getAnHighNegSupport() {
        return 1;
    }

    /**
     * Returns the positive support of the high-pass analysis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * @return The number of taps of the high-pass analysis filter in the
     * positive direction
     * */
    public int getAnHighPosSupport() {
        return 1;
    }

    /**
     * Returns the negative support of the low-pass synthesis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * @return The number of taps of the low-pass synthesis filter in the
     * negative direction
     * */
    public int getSynLowNegSupport() {
        return 1;
    }

    /**
     * Returns the positive support of the low-pass synthesis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * @return The number of taps of the low-pass synthesis filter in the
     * positive direction
     * */
    public int getSynLowPosSupport() {
        return 1;
    }

    /**
     * Returns the negative support of the high-pass synthesis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * @return The number of taps of the high-pass synthesis filter in the
     * negative direction
     * */
    public int getSynHighNegSupport() {
        return 2;
    }

    /**
     * Returns the positive support of the high-pass synthesis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * @return The number of taps of the high-pass synthesis filter in the
     * positive direction
     * */
    public int getSynHighPosSupport() {
        return 2;
    }

    /**
     * Returns the implementation type of this filter, as defined in this
     * class, such as WT_FILTER_INT_LIFT, WT_FILTER_FLOAT_LIFT,
     * WT_FILTER_FLOAT_CONVOL.
     *
     * @return WT_FILTER_INT_LIFT.
     * */
    public int getImplType() {
        return WT_FILTER_INT_LIFT;
    }

    /**
     * Returns the reversibility of the filter. A filter is considered
     * reversible if it is suitable for lossless coding.
     *
     * @return true since the 5x3 is reversible, provided the appropriate
     * rounding is performed.
     * */
    public boolean isReversible() {
        return true; 
    }
    
    /**
     * Returns true if the wavelet filter computes or uses the same "inner"
     * subband coefficient as the full frame wavelet transform, and false
     * otherwise. In particular, for block based transforms with reduced
     * overlap, this method should return false. The term "inner" indicates
     * that this applies only with respect to the coefficient that are not
     * affected by image boundaries processings such as symmetric extension,
     * since there is not reference method for this.
     *
     * <p>The result depends on the length of the allowed overlap when
     * compared to the overlap required by the wavelet filter. It also depends
     * on how overlap processing is implemented in the wavelet filter.</p>
     *
     * @param tailOvrlp This is the number of samples in the input signal
     * before the first sample to filter that can be used for overlap.
     *
     * @param headOvrlp This is the number of samples in the input signal
     * after the last sample to filter that can be used for overlap.
     *
     * @param inLen This is the lenght of the input signal to filter.The
     * required number of samples in the input signal after the last sample
     * depends on the length of the input signal.
     *
     * @return true if both overlaps are greater than 2, and correct
     * processing is applied in the analyze() method.
     * */
    public boolean isSameAsFullWT(int tailOvrlp, int headOvrlp, int inLen) {
        
        //If the input signal has even length.
        if(inLen % 2 == 0) {
            if(tailOvrlp >= 2 && headOvrlp >= 1) return true;
            else return false;
        }
        //Else if the input signal has odd length.
        else {
            if(tailOvrlp >= 2 && headOvrlp >= 2) return true;
            else return false;
        }
    }

    /** 
     * Returns a string of information about the synthesis wavelet filter
     *
     * @return wavelet filter type.
     * */
    public String toString(){
        return "w5x3 (lifting)";
    }
}