Examples with Kernel1D_S32 boofcv.struct.convolve.Kernel1D_S32 used on opensource projects

Example 36 with Kernel1D_S32

use of boofcv.struct.convolve.Kernel1D_S32 in project BoofCV by lessthanoptimal.

the class ConvolveImageMean method horizontal.

/**
 * Performs a horizontal 1D mean box filter. Outside pixels are specified by a border.
 *
 * @param input The input image. Not modified.
 * @param output Where the resulting image is written to. Modified.
 * @param offset Start offset from pixel coordinate
 * @param binput Used to process image borders. If null borders are not processed.
 * @param length How long the mean filter is
 */
public static void horizontal(GrayU8 input, GrayI8 output, int offset, int length, @Nullable ImageBorder_S32<GrayU8> binput) {
    output.reshape(input.width, output.height);
    if (binput != null) {
        binput.setImage(input);
        Kernel1D_S32 kernel = FactoryKernel.table1D_S32(offset, length);
        ConvolveJustBorder_General_SB.horizontal(kernel, binput, output, kernel.computeSum());
    }
    if (length <= input.width) {
        if (BoofConcurrency.USE_CONCURRENT) {
            ImplConvolveMean_MT.horizontal(input, output, offset, length);
        } else {
            ImplConvolveMean.horizontal(input, output, offset, length);
        }
    }
}

Example 37 with Kernel1D_S32

use of boofcv.struct.convolve.Kernel1D_S32 in project BoofCV by lessthanoptimal.

the class BlurImageOps method gaussian.

/**
 * Applies Gaussian blur.
 *
 * @param input Input image. Not modified.
 * @param output (Optional) Storage for output image, Can be null. Modified.
 * @param sigmaX Gaussian distribution's sigma along x-axis. If ≤ 0 then will be selected based on radius.
 * @param radiusX Radius of the Gaussian blur function along x-axis. If ≤ 0 then radius will be determined by sigma.
 * @param sigmaY Gaussian distribution's sigma along y-axis. If ≤ 0 then will be selected based on radius.
 * @param radiusY Radius of the Gaussian blur function along y-axis. If ≤ 0 then radius will be determined by sigma.
 * @param storage (Optional) Storage for intermediate results. Same size as input image. Can be null.
 * @return Output blurred image.
 */
public static InterleavedU8 gaussian(InterleavedU8 input, @Nullable InterleavedU8 output, double sigmaX, int radiusX, double sigmaY, int radiusY, @Nullable InterleavedU8 storage) {
    output = InputSanityCheck.declareOrReshape(input, output);
    storage = InputSanityCheck.declareOrReshape(input, storage);
    boolean processed = BOverrideBlurImageOps.invokeNativeGaussian(input, output, sigmaX, radiusX, sigmaY, radiusY, storage);
    if (!processed) {
        Kernel1D_S32 kernelX = FactoryKernelGaussian.gaussian(Kernel1D_S32.class, sigmaX, radiusX);
        Kernel1D_S32 kernelY = sigmaX == sigmaY && radiusX == radiusY ? kernelX : FactoryKernelGaussian.gaussian(Kernel1D_S32.class, sigmaY, radiusY);
        ConvolveImageNormalized.horizontal(kernelX, input, storage);
        ConvolveImageNormalized.vertical(kernelY, storage, output);
    }
    return output;
}

Example 38 with Kernel1D_S32

use of boofcv.struct.convolve.Kernel1D_S32 in project BoofCV by lessthanoptimal.

the class BlurImageOps method gaussian.

/**
 * Applies Gaussian blur.
 *
 * @param input Input image. Not modified.
 * @param output (Optional) Storage for output image, Can be null. Modified.
 * @param sigmaX Gaussian distribution's sigma along x-axis. If ≤ 0 then will be selected based on radius.
 * @param radiusX Radius of the Gaussian blur function along x-axis. If ≤ 0 then radius will be determined by sigma.
 * @param sigmaY Gaussian distribution's sigma along y-axis. If ≤ 0 then will be selected based on radius.
 * @param radiusY Radius of the Gaussian blur function along y-axis. If ≤ 0 then radius will be determined by sigma.
 * @param storage (Optional) Storage for intermediate results. Same size as input image. Can be null.
 * @return Output blurred image.
 */
public static GrayU16 gaussian(GrayU16 input, @Nullable GrayU16 output, double sigmaX, int radiusX, double sigmaY, int radiusY, @Nullable GrayU16 storage) {
    output = InputSanityCheck.declareOrReshape(input, output);
    storage = InputSanityCheck.declareOrReshape(input, storage);
    boolean processed = BOverrideBlurImageOps.invokeNativeGaussian(input, output, sigmaX, radiusX, sigmaY, radiusY, storage);
    if (!processed) {
        Kernel1D_S32 kernelX = FactoryKernelGaussian.gaussian(Kernel1D_S32.class, sigmaX, radiusX);
        Kernel1D_S32 kernelY = sigmaX == sigmaY && radiusX == radiusY ? kernelX : FactoryKernelGaussian.gaussian(Kernel1D_S32.class, sigmaY, radiusY);
        ConvolveImageNormalized.horizontal(kernelX, input, storage);
        ConvolveImageNormalized.vertical(kernelY, storage, output);
    }
    return output;
}

Example 39 with Kernel1D_S32

use of boofcv.struct.convolve.Kernel1D_S32 in project BoofCV by lessthanoptimal.

the class ConvolveImageBox method horizontal.

/**
 * Performs a horizontal 1D convolution of a box kernel across the image
 *
 * @param input The original image. Not modified.
 * @param output Where the resulting image is written to. Modified.
 * @param radius Kernel size.
 */
public static void horizontal(GrayU8 input, GrayS32 output, int radius) {
    InputSanityCheck.checkSameShape(input, output);
    Kernel1D_S32 kernel = FactoryKernel.table1D_S32(radius);
    ConvolveJustBorder_General_SB.horizontal(kernel, ImageBorderValue.wrap(input, 0), output);
    if (BoofConcurrency.USE_CONCURRENT) {
        ImplConvolveBox_MT.horizontal(input, output, radius);
    } else {
        ImplConvolveBox.horizontal(input, output, radius);
    }
}

Example 40 with Kernel1D_S32

use of boofcv.struct.convolve.Kernel1D_S32 in project BoofCV by lessthanoptimal.

the class ConvolveImageBox method horizontal.

/**
 * Performs a horizontal 1D convolution of a box kernel across the image
 *
 * @param input The original image. Not modified.
 * @param output Where the resulting image is written to. Modified.
 * @param radius Kernel size.
 */
public static void horizontal(GrayS16 input, GrayI16 output, int radius) {
    InputSanityCheck.checkSameShape(input, output);
    Kernel1D_S32 kernel = FactoryKernel.table1D_S32(radius);
    ConvolveJustBorder_General_SB.horizontal(kernel, ImageBorderValue.wrap(input, 0), output);
    if (BoofConcurrency.USE_CONCURRENT) {
        ImplConvolveBox_MT.horizontal(input, output, radius);
    } else {
        ImplConvolveBox.horizontal(input, output, radius);
    }
}