Base Convolution with two kernels. The result is the magnitude of the result of each convolution. \n
* Kernel can be IM_INT or IM_FLOAT, but always IM_GRAY. Use kernel size odd for better results. \n
* Supports all data types. The border is mirrored. \n
* Returns zero if the counter aborted. Most of the convolutions use this function.\n
* If the kernel image attribute "Description" exists it is used by the counter.
*
* \verbatim im.ProcessConvolveDual(src_image: imImage, dst_image: imImage, kernel1, kernel2: imImage) -> counter: boolean [in Lua 5] \endverbatim
* \verbatim im.ProcessConvolveDualNew(image: imImage, kernel1, kernel2: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim
* \ingroup convolve
Base Convolution with two kernels. The result is the magnitude of the result of each convolution. \n * Kernel can be IM_INT or IM_FLOAT, but always IM_GRAY. Use kernel size odd for better results. \n * Supports all data types. The border is mirrored. \n * Returns zero if the counter aborted. Most of the convolutions use this function.\n * If the kernel image attribute "Description" exists it is used by the counter. * * \verbatim im.ProcessConvolveDual(src_image: imImage, dst_image: imImage, kernel1, kernel2: imImage) -> counter: boolean [in Lua 5] \endverbatim * \verbatim im.ProcessConvolveDualNew(image: imImage, kernel1, kernel2: imImage) -> counter: boolean, new_image: imImage [in Lua 5] \endverbatim * \ingroup convolve