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

Example 31 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. Borders are handled by reducing the box size.
 *
 * @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 length How long the mean filter is
 */
public static void horizontal(GrayU16 input, GrayI16 output, int offset, int length) {
    output.reshape(input);
    if (BOverrideConvolveImageMean.invokeNativeHorizontal(input, output, offset, length))
        return;
    Kernel1D_S32 kernel = FactoryKernel.table1D_S32(offset, length);
    if (length > input.width) {
        ConvolveImageNormalized.horizontal(kernel, input, output);
    } else {
        ConvolveNormalized_JustBorder_SB.horizontal(kernel, input, output);
        if (BoofConcurrency.USE_CONCURRENT) {
            ImplConvolveMean_MT.horizontal(input, output, offset, length);
        } else {
            ImplConvolveMean.horizontal(input, output, offset, length);
        }
    }
}

Example 32 with Kernel1D_S32

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

the class ConvolveImageMean method vertical.

/**
 * Performs a vertical 1D mean box filter. Borders are handled by reducing the box size.
 *
 * @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 length How long the mean filter is
 * @param work (Optional) Storage for work array
 */
public static void vertical(GrayU16 input, GrayI16 output, int offset, int length, @Nullable GrowArray<DogArray_I32> workspaces) {
    output.reshape(input);
    if (BOverrideConvolveImageMean.invokeNativeVertical(input, output, offset, length))
        return;
    Kernel1D_S32 kernel = FactoryKernel.table1D_S32(offset, length);
    if (length > input.height) {
        ConvolveImageNormalized.vertical(kernel, input, output);
    } else {
        ConvolveNormalized_JustBorder_SB.vertical(kernel, input, output);
        if (BoofConcurrency.USE_CONCURRENT) {
            ImplConvolveMean_MT.vertical(input, output, offset, length, workspaces);
        } else {
            ImplConvolveMean.vertical(input, output, offset, length, workspaces);
        }
    }
}

Example 33 with Kernel1D_S32

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

the class ConvolveImageMean method vertical.

/**
 * Performs a vertical 1D mean box filter. Borders are handled by reducing the box size.
 *
 * @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 length How long the mean filter is
 * @param work (Optional) Storage for work array
 */
public static void vertical(GrayS16 input, GrayI16 output, int offset, int length, @Nullable GrowArray<DogArray_I32> workspaces) {
    output.reshape(input);
    if (BOverrideConvolveImageMean.invokeNativeVertical(input, output, offset, length))
        return;
    Kernel1D_S32 kernel = FactoryKernel.table1D_S32(offset, length);
    if (length > input.height) {
        ConvolveImageNormalized.vertical(kernel, input, output);
    } else {
        ConvolveNormalized_JustBorder_SB.vertical(kernel, input, output);
        if (BoofConcurrency.USE_CONCURRENT) {
            ImplConvolveMean_MT.vertical(input, output, offset, length, workspaces);
        } else {
            ImplConvolveMean.vertical(input, output, offset, length, workspaces);
        }
    }
}

Example 34 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(GrayU16 input, GrayI16 output, int offset, int length, @Nullable ImageBorder_S32<GrayU16> 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 35 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. Borders are handled by reducing the box size.
 *
 * @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 length How long the mean filter is
 */
public static void horizontal(GrayU8 input, GrayI8 output, int offset, int length) {
    output.reshape(input);
    if (BOverrideConvolveImageMean.invokeNativeHorizontal(input, output, offset, length))
        return;
    Kernel1D_S32 kernel = FactoryKernel.table1D_S32(offset, length);
    if (length > input.width) {
        ConvolveImageNormalized.horizontal(kernel, input, output);
    } else {
        ConvolveNormalized_JustBorder_SB.horizontal(kernel, input, output);
        if (BoofConcurrency.USE_CONCURRENT) {
            ImplConvolveMean_MT.horizontal(input, output, offset, length);
        } else {
            ImplConvolveMean.horizontal(input, output, offset, length);
        }
    }
}