GO-IMG-KERNEL -

GO-IMG-KERNEL is a Go library for image processing, leveraging convolutional operations to perform various transformations such as blurring, edge detection, binarization, and more.

This library aims to provide simple-to-use functions for handling images, whether in RGB or grayscale formats.

Features

• Image loading and saving in various formats (JPEG, PNG).
• Support for RGB and grayscale images.
• Common image transformations:
  • Gaussian blur
  • Edge detection
  • Binarization
  • Image rotation and reflection
  • Horizontal transformation
  • Sharpening

Installation

go get github.com/salamnocap/go-img-kernel

Run Tests

go test -v ./test

Usage

import (
  "github.com/salamnocap/go-img-kernel/utils"
  "github.com/salamnocap/go-img-kernel/transformation"
)

rgbImage, err := utils.LoadRGBImage(
    "../examples/input/castle_rgb.jpg",
) // Load RGB image
if err != nil {
    panic(err)
}
newImage := transformation.BoxBlurRGB(rgbImage, 0, 3) // Apply box blur (0 - padding, 3 -stride)
err = utils.SaveImage(
    newImage,
    "../examples/output/blurred.jpg",
    false,
) // Save image
if err != nil {
    panic(err)
}

Custom Kernel

import (
	"github.com/salamnocap/go-img-kernel/kernel"
    "github.com/salamnocap/go-img-kernel/utils"
)

// Custom kernel
customKernel := kernel.NewKernel(
	3, // Kernel size
    [][]float64{
        {0, -1, 0},
        {-1, 4, -1},
        {0, -1, 0},
    },
)

inputImage, err := utils.LoadRGBImage(
    "../examples/input/castle_rgb.jpg",
) // Load RGB image
if err != nil {
    panic(err)
}

outputImage := kernel.Convolve3D(inputImage, customKernel, 0, 1) // Apply custom kernel (0 - padding, 1 - stride)
err = utils.SaveImage(
    newImage,
    "../examples/output/new_image.jpg",
    false, // if false, save as RGB image
) // Save image
if err != nil {
	panic(err)
}

Examples

Transformation	Kernel Matrix	Input Image	Output Image
Box Blur	$\begin{bmatrix} \frac{1}{9} & \frac{1}{9} & \frac{1}{9} \\ \frac{1}{9} & \frac{1}{9} & \frac{1}{9} \\ \frac{1}{9} & \frac{1}{9} & \frac{1}{9} \end{bmatrix}$
Gaussian Blur	$\begin{bmatrix} \frac{1}{16} & \frac{2}{16} & \frac{1}{16} \\ \frac{2}{16} & \frac{4}{16} & \frac{2}{16} \\ \frac{1}{16} & \frac{2}{16} & \frac{1}{16} \end{bmatrix}$
Edge Detection	$\begin{bmatrix} 0 & -1 & 0 \\ -1 & 4 & -1 \\ 0 & -1 & 0 \end{bmatrix}$
Diagonal Edge Detection	$\begin{bmatrix} 1 & 0 & -1 \\ 0 & 0 & 0 \\ -1 & 0 & 1 \end{bmatrix}$
Binarization	$\begin{bmatrix} 0 & -1 & 0 \\ -1 & 4 & -1 \\ 0 & -1 & 0 \end{bmatrix}$
Image Rotation (45°)	$$-$$
Image Reflection	$\begin{bmatrix} -1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{bmatrix}$
Horizontal Transformation	$\begin{bmatrix} -10 & 10 & -10 \\ 10 & 10 & 10 \\ -10 & 10 & -10 \end{bmatrix}$
Ridge Detection	$\begin{bmatrix} -1 & -1 & -1 \\ -1 & 8 & -1 \\ -1 & -1 & -1 \end{bmatrix}$
Sharpening	$\begin{bmatrix} 0 & -1 & 0 \\ -1 & 5 & -1 \\ 0 & -1 & 0 \end{bmatrix}$