Golang image processing: how to illuminate and remove noise from images

Golang Image Processing: How to illuminate and remove noise from images

Abstract:
In image processing, lighting and denoising are common tasks . This article will introduce how to use Golang for image lighting and denoising. We will use the Go image processing library to implement these functions and provide corresponding code examples.

1. Introduction
   Image processing is one of the important applications in the field of computer vision. Lighting and noise issues are two major challenges that must be faced in image processing. Lighting problems refer to uneven or dim light in the picture, while noise problems refer to interfering pixels in the picture. Addressing these issues can improve the quality and clarity of your images.
2. Light lighting
   Light lighting usually requires adjusting the brightness and contrast of the image. In Golang, we can use the imaging library to implement these functions. Here is a simple example code:

package main

import (
    "fmt"
    "github.com/disintegration/imaging"
    "image"
)

func main() {
    src, err := imaging.Open("input.jpg")
    if err != nil {
        fmt.Println("failed to open image:", err)
        return
    }

    // 调整亮度和对比度
    dst := imaging.AdjustBrightness(src, 20)
    dst = imaging.AdjustContrast(dst, 20)

    err = imaging.Save(dst, "output.jpg")
    if err != nil {
        fmt.Println("failed to save image:", err)
        return
    }

    fmt.Println("image processed successfully")
}

In the above example, we first open an image and use imaging.AdjustBrightness and imaging.AdjustContrast Function to adjust brightness and contrast respectively. Finally, we save the processed image to the output file.

3. Noise Removal
   Noise removal is another common image processing task. In Golang, we can use the goimagehash library to achieve denoising. Here is a simple sample code:

package main

import (
    "fmt"
    "github.com/corona10/goimagehash"
    "image/jpeg"
    "os"
)

func main() {
    file, err := os.Open("input.jpg")
    if err != nil {
        fmt.Println("failed to open image:", err)
        return
    }
    defer file.Close()

    img, err := jpeg.Decode(file)
    if err != nil {
        fmt.Println("failed to decode image:", err)
        return
    }

    // 使用 pHash 方法计算图片的哈希值
    phash, err := goimagehash.PerceptionHash(img)
    if err != nil {
        fmt.Println("failed to calculate hash:", err)
        return
    }

    fmt.Println("original image hash:", phash.GetHash())

    // 使用 AverageHash 方法对图片进行去噪
    ahash, err := goimagehash.AverageHash(img)
    if err != nil {
        fmt.Println("failed to calculate average hash:", err)
        return
    }

    // 输出去噪后的图片的哈希值
    fmt.Println("denoised image hash:", ahash.GetHash())
}

In the above example, we first opened an image and decoded it. Then use goimagehash.PerceptionHash to calculate the hash value of the image, and then use the goimagehash.AverageHash method to denoise the image. Finally, we output the hash value of the denoised image.

Summary:
This article introduces the method of lighting and denoising images in Golang. We can easily implement these functions by using the Go image processing library and goimagehash library. I hope readers can master the lighting and denoising technology in the image processing process through the sample code in this article.

The above is the detailed content of Golang image processing: how to illuminate and remove noise from images. For more information, please follow other related articles on the PHP Chinese website!