unity图片后期处理

Posted 2020-10-04 lipper_

处理算法如下，在Start方法中分别调用想要的效果就行了。其中，将你需要处理的 图片 拖拽到 image参数上。注意，如果想要图片保持原来的尺寸不被压缩，需要更改图片的导入设置如下图，主要的Texture Type 和 Non Power of 2 这两个参数。

 

using UnityEngine;
using System.Collections;
using System.IO;

public class ImageDeal : MonoBehaviour
{
    public Texture2D image;
    private Texture2D outPut;
    int Width;
    int Height;
    // Use this for initialization
    void Start ()
    {
        Width = image.width;
        Height = image.height;
        outPut = new Texture2D (Width, Height);
        Flur ();

        writeImage ();
    }

    /// <summary>
    /// 底片效果.
    /// </summary>
    private void Dipian ()
    {
        Color pixel;
        for (int x = 1; x < Width; x++) {
            for (int y = 1; y < Height; y++) {
                float r, g, b;
                pixel = image.GetPixel (x, y);
                r = 1f - pixel.r;
                g = 1f - pixel.g;
                b = 1f - pixel.b;
                outPut.SetPixel (x, y, new Color (r, g, b));
            }
        }
    }

    /// <summary>
    /// 浮雕效果
    /// </summary>
    private void Fudiao ()
    {
        //以浮雕效果显示图像
        Color pixel1, pixel2;
        for (int x = 0; x < Width - 1; x++) {
            for (int y = 0; y < Height - 1; y++) {
                float r = 0, g = 0, b = 0;
                pixel1 = image.GetPixel (x, y);
                pixel2 = image.GetPixel (x + 1, y + 1);
                r = Mathf.Abs (pixel1.r - pixel2.r + 128 / 255);
                g = Mathf.Abs (pixel1.g - pixel2.g + 128 / 255);
                b = Mathf.Abs (pixel1.b - pixel2.b + 128 / 255);
            
                outPut.SetPixel (x, y, new Color (r, g, b));
            }
        }

    }
    /// <summary>
    /// 黑白效果
    /// </summary>
    private void Heibai(){
        Color pixel;
        for (int x = 0; x < Width; x++)
            for (int y = 0; y < Height; y++) {
                pixel = image.GetPixel (x, y);
                float r, g, b, Result = 0;
                r = pixel.r;
                g = pixel.g;
                b = pixel.b;
                //实例程序以加权平均值法产生黑白图像
                int iType = 2;
                switch (iType) {
                case 0://平均值法
                    Result = ((r + g + b) / 3);
                    break;
                case 1://最大值法
                    Result = r > g ? r : g;
                    Result = Result > b ? Result : b;
                    break;
                case 2://加权平均值法
                    Result = ((0.7f * r) + (0.2f * g) + (0.1f * b));
                    break;
                }
                outPut.SetPixel (x, y, new Color (Result, Result, Result));
            }
    }
    /// <summary>
    /// 柔化3x3高斯模型
    /// </summary>
    private void Rouhua3(){
        Color pixel;
        int[] Gauss ={ 1, 2, 1, 2, 4, 2, 1, 2, 1 };
        for (int x = 1; x < Width - 1; x++)
            for (int y = 1; y < Height - 1; y++)
            {
                float r = 0, g = 0, b = 0;
                int Index = 0;
                for (int col = -1; col <= 1; col++)
                    for (int row = -1; row <= 1; row++)
                    {
                        pixel = image.GetPixel(x + row, y + col);
                        r += pixel.r * Gauss[Index];
                        g += pixel.g * Gauss[Index];
                        b += pixel.b * Gauss[Index];
                        Index++;
                    }
                r /= 16;
                g /= 16;
                b /= 16;
                outPut.SetPixel(x - 1, y - 1, new Color(r, g, b));
            }
    }
    /// <summary>
    /// 柔化5x5高斯模型
    /// </summary>
    private void Rouhua5(){
        Color pixel;
        int[] Gauss = { 1, 4, 7, 4, 1, 4, 16, 26, 16, 4, 7, 26, 41, 26, 7, 4, 16, 26, 16, 4, 1, 4, 7, 4, 1 };
        for (int x = 1; x < Width - 1; x++)
            for (int y = 1; y < Height - 1; y++)
            {
                float r = 0, g = 0, b = 0;
                int Index = 0;
                for (int col = -2; col <= 2; col++)
                    for (int row = -2; row <= 2; row++)
                    {
                        pixel = image.GetPixel(x + row, y + col);
                        r += pixel.r * Gauss[Index];
                        g += pixel.g * Gauss[Index];
                        b += pixel.b * Gauss[Index];
                        Index++;
                    }
                r /= 273;
                g /= 273;
                b /= 273;
                outPut.SetPixel(x - 1, y - 1, new Color(r, g, b));
            }
    }
    /// <summary>
    /// 柔化，高斯模糊通用方法
    /// </summary>
    private void Flur(){
        Color pixel;
        float[] Gauss = GaussianSmooth (10.0f);
        for (int x = 1; x < Width - 1; x++)
            for (int y = 1; y < Height - 1; y++)
            {
                float r = 0, g = 0, b = 0;
                int Index = 0;
                int length = (int)Mathf.Sqrt (Gauss.Length) / 2;
                for (int col = -length; col <= length; col++)
                    for (int row = -length; row <= length; row++)
                    {
                        pixel = image.GetPixel(x + row, y + col);
                        r += pixel.r * Gauss[Index];
                        g += pixel.g * Gauss[Index];
                        b += pixel.b * Gauss[Index];
                        Index++;
                    }
                outPut.SetPixel(x - 1, y - 1, new Color(r, g, b));
            }
    }
    /// <summary>
    /// 锐化效果
    /// </summary>
    private void Ruihua(){
        Color pixel;
        //拉普拉斯模板
        int[] Laplacian ={ -1, -1, -1, -1, 9, -1, -1, -1, -1 };
        for (int x = 1; x < Width - 1; x++)
            for (int y = 1; y < Height - 1; y++)
            {
                float r = 0, g = 0, b = 0;
                int Index = 0;
                for (int col = -1; col <= 1; col++)
                    for (int row = -1; row <= 1; row++)
                    {
                        pixel = image.GetPixel(x + row, y + col); 
                        r += pixel.r * Laplacian[Index];
                        g += pixel.g * Laplacian[Index];
                        b += pixel.b * Laplacian[Index];
                        Index++;
                    }
                outPut.SetPixel(x - 1, y - 1, new Color(r, g, b));
            }
    }
    /// <summary>
    /// 写文件
    /// </summary>
    private void writeImage ()
    {
        byte[] bytes = outPut.EncodeToJPG ();
        File.WriteAllBytes (Application.dataPath + "/test.jpg", bytes);
    }
        
    /// <summary>
    /// 动态生成高斯模型
    /// </summary>
    /// <returns>The smooth.</returns>
    /// <param name="sigma">Sigma.</param>
    private float[] GaussianSmooth( float sigma)  
    {   
        sigma = sigma > 0 ? sigma : -sigma;  
        //高斯核矩阵的大小为(6*sigma+1)*(6*sigma+1)  
        //ksize为奇数  
        int ksize = (int)Mathf.Ceil(sigma * 3) * 2 + 1;   

        //计算一维高斯核  
        float[] kernel = new float[ksize];  

        float scale = -0.5f / (sigma * sigma);
        const float PI = 3.141592653f;  
        float cons = 1/ Mathf.Sqrt(-scale / PI);  

        float sum = 0;  
        int kcenter = ksize/2;  
        int i = 0, j = 0;  
        for(i = 0; i < ksize; i++)  
        {  
            int x = i - kcenter;  
            kernel[i] = cons * Mathf.Exp(x * x * scale);//一维高斯函数  
            sum +=kernel[i];  
  
        }   
        //归一化,确保高斯权值在[0,1]之间  
        for(i = 0; i < ksize; i++)  
        {  
            kernel[i] =  kernel[i] / sum;
        }   
        return kernel;
    }
}