synwtfilterfloatlift9x7.java

jpeg2000编解码

        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
        
        // Initialize counters
        lk = lowOff;
        hk = highOff;
        
        if(outLen!=1) {
	    int outLen2 = outLen>>1;
            // "Inverse normalize" each sample
            for(i=0; i<outLen2; i++) {
                lowSig[lk] /= KL;
                highSig[hk] /= KH;
                lk += lowStep;  
                hk += highStep;
            } 
            // "Inverse normalise" last high pass coefficient
            if(outLen%2==1) {
		highSig[hk] /= KH;
            }
        } else {
	    // Normalize for Nyquist gain
	    highSig[highOff] /= 2;
	}
        
        // Generate intermediate low frequency subband
        
        //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] - 
                DELTA*(highSig[hk] + highSig[hk+highStep]);
            ik += iStep;
            lk += lowStep;
            hk += highStep;
        }
        
        if(outLen%2==0 && outLen>1) {
            //Use symmetric extension
            outSig[ik] = lowSig[lk] - 2*DELTA*highSig[hk];
        }
        
        // Generate intermediate high frequency subband
         
        //Initialize counters
        hk = highOff;
        ik = outOff;
        
        if(outLen>1) {
            outSig[ik] = highSig[hk] - 2*GAMMA*outSig[ik+outStep];
        } else {
            outSig[ik] = highSig[hk];
        }
            
        ik += iStep;
        hk += highStep;
            
        //Apply lifting step to each "inner" sample
        for(i=2; i<outLen-1; i+=2 ) {
            outSig[ik] = highSig[hk] - 
                GAMMA*(outSig[ik-outStep] + outSig[ik+outStep]);
            ik += iStep;
            hk += highStep;
        }

        //Handle head boundary effect if output signal has even length
        if(outLen%2==1 && outLen>1) {
            //Use symmetric extension
            outSig[ik] = highSig[hk] - 2*GAMMA*outSig[ik-outStep];
        }        

        // Generate even samples (inverse low-pass filter)

        //Initialize counters
        ik = outOff + outStep;
    
        //Apply lifting step to each "inner" sample
        for(i=1; i<outLen-1; i+=2 ) {
            outSig[ik] -= BETA*(outSig[ik-outStep] + outSig[ik+outStep]);
            ik += iStep;
        }
        
        if(outLen%2==0 && outLen>1) { 
            // symmetric extension.
            outSig[ik] -= 2*BETA*outSig[ik-outStep];
        }
        
        // Generate odd samples (inverse high pass-filter)
         
        //Initialize counters
        ik = outOff;

        if(outLen>1) {
            // symmetric extension.
            outSig[ik] -= 2*ALPHA*outSig[ik+outStep];
        }
        ik += iStep;
        
        //Apply first lifting step to each "inner" sample
        for(i=2; i<outLen-1 ; i+=2) { 
            outSig[ik] -= ALPHA*(outSig[ik-outStep] + outSig[ik+outStep]);
            ik += iStep;
        }
        
        //Handle head boundary effect if input signal has even length
        if((outLen%2==1) && (outLen>1)) {
            //Use symmetric extension 
            outSig[ik] -= 2*ALPHA*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 4;
    }

    /**
     * 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 4;
    }

    /**
     * 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 3;
    }

    /**
     * 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 3;
    }

    /**
     * Returns the negative support of the low-pass synthesis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * <P>A MORE PRECISE DEFINITION IS NEEDED
     *
     * @return The number of taps of the low-pass synthesis filter in the
     * negative direction
     * */
    public int getSynLowNegSupport() {
        return 3;
    }

    /**
     * Returns the positive support of the low-pass synthesis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * <P>A MORE PRECISE DEFINITION IS NEEDED
     *
     * @return The number of taps of the low-pass synthesis filter in the
     * positive direction
     * */
    public int getSynLowPosSupport() {
        return 3;
    }

    /**
     * Returns the negative support of the high-pass synthesis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * <P>A MORE PRECISE DEFINITION IS NEEDED
     *
     * @return The number of taps of the high-pass synthesis filter in the
     * negative direction
     * */
    public int getSynHighNegSupport() {
        return 4;
    }

    /**
     * Returns the positive support of the high-pass synthesis filter. That is
     * the number of taps of the filter in the negative direction.
     *
     * <P>A MORE PRECISE DEFINITION IS NEEDED
     *
     * @return The number of taps of the high-pass synthesis filter in the
     * positive direction
     * */
    public int getSynHighPosSupport() {
        return 4;
    }

    /**
     * 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_FLOAT_LIFT;
    }

    /**
     * Returns the reversibility of the filter. A filter is considered
     * reversible if it is suitable for lossless coding.
     *
     * @return true since the 9x7 is reversible, provided the appropriate
     * rounding is performed.
     * */
    public boolean isReversible() {
        return false; 
    }
    
    /**
     * 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.
     *
     * @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 "w9x7 (lifting)";
    }
}