cvsmooth.cpp

opencv库在TI DM6437上的移植,目前包括两个库cv.lib和cxcore.lib的工程

#define UPDATE_OUTPUT_C3\
            mean0 = 1./mean0;\
            dst[i*3 + 0] = (uchar)cvRound(mean1[0]*mean0); \
            dst[i*3 + 1] = (uchar)cvRound(mean1[1]*mean0); \
            dst[i*3 + 2] = (uchar)cvRound(mean1[2]*mean0);

    CV_INIT_3X3_DELTAS( deltas, srcStep, channels );

    weight_tab[0] = weight_tab[2] = weight_tab[4] = weight_tab[6] = i2sigma_space;
    weight_tab[1] = weight_tab[3] = weight_tab[5] = weight_tab[7] = i2sigma_space*2;

    if( channels == 1 )
    {
        int color, temp_color;

        for( i = 0; i < size.width; i++, src++ )
        {
            INIT_C1;
            KERNEL_ELEMENT_C1(6);
            if( i > 0 )
            {
                KERNEL_ELEMENT_C1(5);
                KERNEL_ELEMENT_C1(4);
            }
            if( i < size.width - 1 )
            {
                KERNEL_ELEMENT_C1(7);
                KERNEL_ELEMENT_C1(0);
            }
            UPDATE_OUTPUT_C1;
        }

        src += srcStep - size.width;
        dst += dstStep;

        for( j = 1; j < size.height - 1; j++, dst += dstStep )
        {
            i = 0;
            INIT_C1;
            KERNEL_ELEMENT_C1(0);
            KERNEL_ELEMENT_C1(1);
            KERNEL_ELEMENT_C1(2);
            KERNEL_ELEMENT_C1(6);
            KERNEL_ELEMENT_C1(7);
            UPDATE_OUTPUT_C1;

            for( i = 1, src++; i < size.width - 1; i++, src++ )
            {
                INIT_C1;
                KERNEL_ELEMENT_C1(0);
                KERNEL_ELEMENT_C1(1);
                KERNEL_ELEMENT_C1(2);
                KERNEL_ELEMENT_C1(3);
                KERNEL_ELEMENT_C1(4);
                KERNEL_ELEMENT_C1(5);
                KERNEL_ELEMENT_C1(6);
                KERNEL_ELEMENT_C1(7);
                UPDATE_OUTPUT_C1;
            }

            INIT_C1;
            KERNEL_ELEMENT_C1(2);
            KERNEL_ELEMENT_C1(3);
            KERNEL_ELEMENT_C1(4);
            KERNEL_ELEMENT_C1(5);
            KERNEL_ELEMENT_C1(6);
            UPDATE_OUTPUT_C1;

            src += srcStep + 1 - size.width;
        }

        for( i = 0; i < size.width; i++, src++ )
        {
            INIT_C1;
            KERNEL_ELEMENT_C1(2);
            if( i > 0 )
            {
                KERNEL_ELEMENT_C1(3);
                KERNEL_ELEMENT_C1(4);
            }
            if( i < size.width - 1 )
            {
                KERNEL_ELEMENT_C1(1);
                KERNEL_ELEMENT_C1(0);
            }
            UPDATE_OUTPUT_C1;
        }
    }
    else
    {
        uchar* temp_color;

        if( channels != 3 )
            return CV_UNSUPPORTED_CHANNELS_ERR;

        for( i = 0; i < size.width; i++, src += 3 )
        {
            INIT_C3;
            KERNEL_ELEMENT_C3(6);
            if( i > 0 )
            {
                KERNEL_ELEMENT_C3(5);
                KERNEL_ELEMENT_C3(4);
            }
            if( i < size.width - 1 )
            {
                KERNEL_ELEMENT_C3(7);
                KERNEL_ELEMENT_C3(0);
            }
            UPDATE_OUTPUT_C3;
        }

        src += srcStep - size.width*3;
        dst += dstStep;

        for( j = 1; j < size.height - 1; j++, dst += dstStep )
        {
            i = 0;
            INIT_C3;
            KERNEL_ELEMENT_C3(0);
            KERNEL_ELEMENT_C3(1);
            KERNEL_ELEMENT_C3(2);
            KERNEL_ELEMENT_C3(6);
            KERNEL_ELEMENT_C3(7);
            UPDATE_OUTPUT_C3;

            for( i = 1, src += 3; i < size.width - 1; i++, src += 3 )
            {
                INIT_C3;
                KERNEL_ELEMENT_C3(0);
                KERNEL_ELEMENT_C3(1);
                KERNEL_ELEMENT_C3(2);
                KERNEL_ELEMENT_C3(3);
                KERNEL_ELEMENT_C3(4);
                KERNEL_ELEMENT_C3(5);
                KERNEL_ELEMENT_C3(6);
                KERNEL_ELEMENT_C3(7);
                UPDATE_OUTPUT_C3;
            }

            INIT_C3;
            KERNEL_ELEMENT_C3(2);
            KERNEL_ELEMENT_C3(3);
            KERNEL_ELEMENT_C3(4);
            KERNEL_ELEMENT_C3(5);
            KERNEL_ELEMENT_C3(6);
            UPDATE_OUTPUT_C3;

            src += srcStep + 3 - size.width*3;
        }

        for( i = 0; i < size.width; i++, src += 3 )
        {
            INIT_C3;
            KERNEL_ELEMENT_C3(2);
            if( i > 0 )
            {
                KERNEL_ELEMENT_C3(3);
                KERNEL_ELEMENT_C3(4);
            }
            if( i < size.width - 1 )
            {
                KERNEL_ELEMENT_C3(1);
                KERNEL_ELEMENT_C3(0);
            }
            UPDATE_OUTPUT_C3;
        }
    }

    return CV_OK;
#undef INIT_C1
#undef KERNEL_ELEMENT_C1
#undef UPDATE_OUTPUT_C1
#undef INIT_C3
#undef KERNEL_ELEMENT_C3
#undef UPDATE_OUTPUT_C3
#undef COLOR_DISTANCE_C3
}

//////////////////////////////// IPP smoothing functions /////////////////////////////////

icvFilterMedian_8u_C1R_t icvFilterMedian_8u_C1R_p = 0;
icvFilterMedian_8u_C3R_t icvFilterMedian_8u_C3R_p = 0;
icvFilterMedian_8u_C4R_t icvFilterMedian_8u_C4R_p = 0;

icvFilterBox_8u_C1R_t icvFilterBox_8u_C1R_p = 0;
icvFilterBox_8u_C3R_t icvFilterBox_8u_C3R_p = 0;
icvFilterBox_8u_C4R_t icvFilterBox_8u_C4R_p = 0;
icvFilterBox_32f_C1R_t icvFilterBox_32f_C1R_p = 0;
icvFilterBox_32f_C3R_t icvFilterBox_32f_C3R_p = 0;
icvFilterBox_32f_C4R_t icvFilterBox_32f_C4R_p = 0;

typedef CvStatus (CV_STDCALL * CvSmoothFixedIPPFunc)
( const void* src, int srcstep, void* dst, int dststep,
  CvSize size, CvSize ksize, CvPoint anchor );

//////////////////////////////////////////////////////////////////////////////////////////

CV_IMPL void
cvSmooth( const void* srcarr, void* dstarr, int smooth_type,
          int param1, int param2, double param3, double param4 )
{
    CvBoxFilter box_filter;
    CvSepFilter gaussian_filter;

    CvMat* temp = 0;

    CV_FUNCNAME( "cvSmooth" );

    __BEGIN__;

    int coi1 = 0, coi2 = 0;
    CvMat srcstub, *src = (CvMat*)srcarr;
    CvMat dststub, *dst = (CvMat*)dstarr;
    CvSize size;
    int src_type, dst_type, depth, cn;
    double sigma1 = 0, sigma2 = 0;
    bool have_ipp = icvFilterMedian_8u_C1R_p != 0;

    CV_CALL( src = cvGetMat( src, &srcstub, &coi1 ));
    CV_CALL( dst = cvGetMat( dst, &dststub, &coi2 ));

    if( coi1 != 0 || coi2 != 0 )
        CV_ERROR( CV_BadCOI, "" );

    src_type = CV_MAT_TYPE( src->type );
    dst_type = CV_MAT_TYPE( dst->type );
    depth = CV_MAT_DEPTH(src_type);
    cn = CV_MAT_CN(src_type);
    size = cvGetMatSize(src);

    if( !CV_ARE_SIZES_EQ( src, dst ))
        CV_ERROR( CV_StsUnmatchedSizes, "" );

    if( smooth_type != CV_BLUR_NO_SCALE && !CV_ARE_TYPES_EQ( src, dst ))
        CV_ERROR( CV_StsUnmatchedFormats,
        "The specified smoothing algorithm requires input and ouput arrays be of the same type" );

    if( smooth_type == CV_BLUR || smooth_type == CV_BLUR_NO_SCALE ||
        smooth_type == CV_GAUSSIAN || smooth_type == CV_MEDIAN )
    {
        // automatic detection of kernel size from sigma
        if( smooth_type == CV_GAUSSIAN )
        {
            sigma1 = param3;
            sigma2 = param4 ? param4 : param3;

            if( param1 == 0 && sigma1 > 0 )
                param1 = cvRound(sigma1*(depth == CV_8U ? 3 : 4)*2 + 1)|1;
            if( param2 == 0 && sigma2 > 0 )
                param2 = cvRound(sigma2*(depth == CV_8U ? 3 : 4)*2 + 1)|1;
        }

        if( param2 == 0 )
            param2 = size.height == 1 ? 1 : param1;
        if( param1 < 1 || (param1 & 1) == 0 || param2 < 1 || (param2 & 1) == 0 )
            CV_ERROR( CV_StsOutOfRange,
                "Both mask width and height must be >=1 and odd" );

        if( param1 == 1 && param2 == 1 )
        {
            cvConvert( src, dst );
            EXIT;
        }
    }

    if( have_ipp && (smooth_type == CV_BLUR || smooth_type == CV_MEDIAN) &&
        size.width >= param1 && size.height >= param2 && param1 > 1 && param2 > 1 )
    {
        CvSmoothFixedIPPFunc ipp_median_box_func = 0;

        if( smooth_type == CV_BLUR )
        {
            ipp_median_box_func =
                src_type == CV_8UC1 ? icvFilterBox_8u_C1R_p :
                src_type == CV_8UC3 ? icvFilterBox_8u_C3R_p :
                src_type == CV_8UC4 ? icvFilterBox_8u_C4R_p :
                src_type == CV_32FC1 ? icvFilterBox_32f_C1R_p :
                src_type == CV_32FC3 ? icvFilterBox_32f_C3R_p :
                src_type == CV_32FC4 ? icvFilterBox_32f_C4R_p : 0;
        }
        else if( smooth_type == CV_MEDIAN )
        {
            ipp_median_box_func =
                src_type == CV_8UC1 ? icvFilterMedian_8u_C1R_p :
                src_type == CV_8UC3 ? icvFilterMedian_8u_C3R_p :
                src_type == CV_8UC4 ? icvFilterMedian_8u_C4R_p : 0;
        }

        if( ipp_median_box_func )
        {
            CvSize el_size = { param1, param2 };
            CvPoint el_anchor = { param1/2, param2/2 };
            int stripe_size = 1 << 14; // the optimal value may depend on CPU cache,
                                       // overhead of the current IPP code etc.
            const uchar* shifted_ptr;
            int y, dy = 0;
            int temp_step, dst_step = dst->step;

            CV_CALL( temp = icvIPPFilterInit( src, stripe_size, el_size ));

            shifted_ptr = temp->data.ptr +
                el_anchor.y*temp->step + el_anchor.x*CV_ELEM_SIZE(src_type);
            temp_step = temp->step ? temp->step : CV_STUB_STEP;

            for( y = 0; y < src->rows; y += dy )
            {
                dy = icvIPPFilterNextStripe( src, temp, y, el_size, el_anchor );
                IPPI_CALL( ipp_median_box_func( shifted_ptr, temp_step,
                    dst->data.ptr + y*dst_step, dst_step, cvSize(src->cols, dy),
                    el_size, el_anchor ));
            }
            EXIT;
        }
    }

    if( smooth_type == CV_BLUR || smooth_type == CV_BLUR_NO_SCALE )
    {
        CV_CALL( box_filter.init( src->cols, src_type, dst_type,
            smooth_type == CV_BLUR, cvSize(param1, param2) ));
        CV_CALL( box_filter.process( src, dst ));
    }
    else if( smooth_type == CV_MEDIAN )
    {
        if( depth != CV_8U || cn != 1 && cn != 3 && cn != 4 )
            CV_ERROR( CV_StsUnsupportedFormat,
            "Median filter only supports 8uC1, 8uC3 and 8uC4 images" );

        IPPI_CALL( icvMedianBlur_8u_CnR( src->data.ptr, src->step,
            dst->data.ptr, dst->step, size, param1, cn ));
    }
    else if( smooth_type == CV_GAUSSIAN )
    {
        CvSize ksize = { param1, param2 };
        float* kx = (float*)cvStackAlloc( ksize.width*sizeof(kx[0]) );
        float* ky = (float*)cvStackAlloc( ksize.height*sizeof(ky[0]) );
        CvMat KX = cvMat( 1, ksize.width, CV_32F, kx );
        CvMat KY = cvMat( 1, ksize.height, CV_32F, ky );
        
        CvSepFilter::init_gaussian_kernel( &KX, sigma1 );
        if( ksize.width != ksize.height || fabs(sigma1 - sigma2) > FLT_EPSILON )
            CvSepFilter::init_gaussian_kernel( &KY, sigma2 );
        else
            KY.data.fl = kx;
        
        if( have_ipp && size.width >= param1*3 &&
            size.height >= param2 && param1 > 1 && param2 > 1 )
        {
            int done;
            CV_CALL( done = icvIPPSepFilter( src, dst, &KX, &KY,
                        cvPoint(ksize.width/2,ksize.height/2)));
            if( done )
                EXIT;
        }

        CV_CALL( gaussian_filter.init( src->cols, src_type, dst_type, &KX, &KY ));
        CV_CALL( gaussian_filter.process( src, dst ));
    }
    else if( smooth_type == CV_BILATERAL )
    {
        if( param1 < 0 || param2 < 0 )
            CV_ERROR( CV_StsOutOfRange,
            "Thresholds in bilaral filtering should not bee negative" );
        param1 += param1 == 0;
        param2 += param2 == 0;

        if( depth != CV_8U || cn != 1 && cn != 3 )
            CV_ERROR( CV_StsUnsupportedFormat,
            "Bilateral filter only supports 8uC1 and 8uC3 images" );

        IPPI_CALL( icvBilateralFiltering_8u_CnR( src->data.ptr, src->step,
            dst->data.ptr, dst->step, size, param1, param2, cn ));
    }

    __END__;

    cvReleaseMat( &temp );
}

/* End of file. */