ImagickKernel::addUnityKernel Description &reftitle.description; public voidImagickKernel::addUnityKernel floatscale Adds a given amount of the 'Unity' Convolution Kernel to the given pre-scaled and normalized Kernel. This in effect adds that amount of the original image into the resulting convolution kernel. The resulting effect is to convert the defined kernels into blended soft-blurs, unsharp kernels or into sharpening kernels. &reftitle.parameters; &no.function.parameters; &reftitle.returnvalues; &reftitle.examples; "; foreach ($matrix as $row) { $output .= ""; foreach ($row as $cell) { $output .= ""; if ($cell === false) { $output .= "false"; } else { $output .= round($cell, 3); } $output .= ""; } $output .= ""; } $output .= ""; return $output; } $matrix = [ [-1, 0, -1], [ 0, 4, 0], [-1, 0, -1], ]; $kernel = \ImagickKernel::fromMatrix($matrix); $kernel->scale(1, \Imagick::NORMALIZE_KERNEL_VALUE); $output = "Before adding unity kernel:
"; $output .= renderKernelTable($kernel->getMatrix()); $kernel->addUnityKernel(0.5); $output .= "After adding unity kernel:
"; $output .= renderKernelTable($kernel->getMatrix()); $kernel->scale(1, \Imagick::NORMALIZE_KERNEL_VALUE); $output .= "After renormalizing kernel:
"; $output .= renderKernelTable($kernel->getMatrix()); echo $output; ?> ]]> scale(4, \Imagick::NORMALIZE_KERNEL_VALUE); $kernel->addUnityKernel(0.5); $imagick = new \Imagick(realpath($imagePath)); $imagick->filter($kernel); header("Content-Type: image/jpg"); echo $imagick->getImageBlob(); } ?> ]]>