applyfilt

applyfilt is a term used in image and signal processing to describe a function that applies a filter to an input data set. In practice it typically performs a convolution or correlation with a user-supplied kernel, producing a filtered output. The function is generic and appears in many libraries as part of filtering workflows.

Inputs usually include the data array (which can be 1D signals, 2D images, or 3D volumes) and the filter kernel (a 1D vector or a 2D/3D matrix). Optional parameters control boundary handling (padding modes such as zero, reflect, or replicate), output size (same as input or reduced), stride, and dilation. For multi-channel data, filtering can be applied per channel or jointly, depending on the implementation. Some variants normalize the kernel so its sum is one to preserve magnitude.

Implementation options include direct spatial convolution, FFT-based methods for large kernels, or separable filters that decompose into successive 1D passes. Boundary effects, padding, and data type can influence results. The function may return the same size as the input when padding is used, or a smaller array in “valid” mode.

Applications include smoothing, sharpening, blur, edge detection, and noise reduction. It is a common building block in computer vision, image processing pipelines, and audio processing. Because the name and exact behavior vary by library, users should consult specific documentation for parameter naming and default values.