new FFTConvolution< FloatType >( image2, kernel ); c.convolve();
new FFTConvolution< FloatType >( image2, kernel ); c.convolve();
public static Img< FloatType > convolve( final Img< FloatType > img, final Img< FloatType > psf ) { Tools.normImage( psf ); final Img< FloatType > result = img.factory().create( img, img.firstElement() ); final FFTConvolution< FloatType > conv = new FFTConvolution<FloatType>( img, psf, result ); // this fixes the wrong default kernel flipping in older versions of FFTConvolution conv.setComputeComplexConjugate(false); conv.convolve(); return result; }
final FFTConvolution< FloatType > fftconv = new FFTConvolution<>( floatImg, kernel );
final FFTConvolution< FloatType > fftconv = new FFTConvolution<>( floatImg, kernel );
new FFTConvolution< FloatType >( image2, kernel ); c.convolve();
new FFTConvolution< FloatType >( image2, kernel ); c.convolve();
new FFTConvolution< FloatType >( image2, kernel ); c.convolve();
FFTConvolution< FloatType > fftConv = new FFTConvolution<FloatType>( input, createGaussianKernel( sigma1 ), conv, imgFactory ); fftConv.convolve(); fftConv = new FFTConvolution<FloatType>( conv, createGaussianKernel( sigma2 ), imgFactory ); fftConv.convolve();
new FFTConvolution< FloatType >( image2, kernel ); c.convolve();