基于C语言的数字图像处理实验源码（课程大作业）.zip

#include<stdio.h> #include<malloc.h> #include<stdlib.h> /* 位图头结构 */ #pragma pack(1) typedef struct tagBITMAPFILEHEADER { unsigned char bfType[2];//文件格式 unsigned long bfSize;//文件大小 unsigned short bfReserved1;//保留 unsigned short bfReserved2; unsigned long bfOffBits; //DIB数据在文件中的偏移量 }fileHeader; #pragma pack() /* 位图数据信息结构 */ #pragma pack(1) typedef struct tagBITMAPINFOHEADER { unsigned long biSize;//该结构的大小 long biWidth;//文件宽度 long biHeight;//文件高度 unsigned short biPlanes;//平面数 unsigned short biBitCount;//颜色位数 unsigned long biCompression;//压缩类型 unsigned long biSizeImage;//DIB数据区大小 long biXPixPerMeter; long biYPixPerMeter; unsigned long biClrUsed;//多少颜色索引表 unsigned long biClrImporant;//多少重要颜色 }fileInfo; #pragma pack() /* 调色板结构 */ #pragma pack(1) typedef struct tagRGBQUAD { unsigned char rgbBlue; //蓝色分量亮度 unsigned char rgbGreen;//绿色分量亮度 unsigned char rgbRed;//红色分量亮度 unsigned char rgbReserved; }rgbq; #pragma pack() void avgSmoothing(unsigned char ** ImgData, unsigned char ** ImgData2, int ImgWidth, int ImgHeight); void midSmoothing(unsigned char ** ImgData, unsigned char ** ImgData2, int ImgWidth, int ImgHeight); int main() { int i, j, k; FILE * fpBMP, *fpSmooth; fileHeader * fh; fileInfo * fi; rgbq * fq; if ((fpBMP = fopen("D:/bmpTest/32.bmp", "rb")) == NULL) { printf("打开文件失败"); exit(0); } if ((fpSmooth = fopen("D:/bmpTest/34.bmp", "wb")) == NULL) { printf("创建文件失败"); exit(0); } fh = (fileHeader *)malloc(sizeof(fileHeader)); fi = (fileInfo *)malloc(sizeof(fileInfo)); //读取位图头结构和信息头 fread(fh, sizeof(fileHeader), 1, fpBMP); fread(fi, sizeof(fileInfo), 1, fpBMP); //修改头信息 fi->biBitCount = 8; fi->biSizeImage = ((fi->biWidth * 3 + 3) / 4) * 4 * fi->biHeight; fh->bfOffBits = sizeof(fileHeader)+sizeof(fileInfo)+256 * sizeof(rgbq); fh->bfSize = fh->bfOffBits + fi->biSizeImage; //创建调色版 fq = (rgbq *)malloc(256 * sizeof(rgbq)); for (i = 0; i<256; i++) { fq[i].rgbBlue = fq[i].rgbGreen = fq[i].rgbRed = i; } //将头信息写入 fwrite(fh, sizeof(fileHeader), 1, fpSmooth); fwrite(fi, sizeof(fileInfo), 1, fpSmooth); fwrite(fq, sizeof(rgbq), 256, fpSmooth); //8位图像不读取颜色查找表. fseek(fpBMP, sizeof(rgbq)* 256, SEEK_CUR); long ImgWidth = fi->biWidth; long ImgHeight = fi->biHeight; unsigned char ** ImgData;//存储原图像的每个点的灰度值. unsigned char ** ImgData2;//滤波后每个像素点的灰度值. ImgData = (unsigned char **)malloc(sizeof(unsigned char*)*ImgHeight); ImgData2 = (unsigned char **)malloc(sizeof(unsigned char*)*ImgHeight); for (int i = 0; i < fi->biHeight; i++) { ImgData[i] = (unsigned char*)malloc(sizeof(unsigned char*)*ImgWidth); ImgData2[i] = (unsigned char*)malloc(sizeof(unsigned char*)*ImgWidth); } for (i = 0; i < ImgHeight; i++) { for (j = 0; j < (ImgWidth + 3) / 4 * 4; j++) { //读取灰度值. fread(&ImgData[i][j], 1, 1, fpBMP); } } //avgSmoothing(ImgData, ImgData2, ImgWidth, ImgHeight); midSmoothing(ImgData, ImgData2, ImgWidth, ImgHeight); //将灰度图信息写入 for (int i = 0; i < ImgHeight; i++) { fwrite(ImgData2[i], ImgWidth, 1, fpSmooth); } free(fh); free(fi); free(fq); fclose(fpBMP); fclose(fpSmooth); printf("success\n"); return 0; } //均值滤波器. //ImgData:原图像数据 ImgData2:滤波后的图像数据 ImgWidth:图像宽度 ImgHeight:图像高度 void avgSmoothing(unsigned char ** ImgData, unsigned char ** ImgData2, int ImgWidth, int ImgHeight) { //对图像的四个角点操作. ImgData2[0][0] = (unsigned char)((float)(ImgData[0][0] + ImgData[0][1] + ImgData[1][0] + ImgData[1][1]) / 4 + 0.5); ImgData2[0][ImgWidth - 1] = (unsigned char)((float)(ImgData[0][ImgWidth - 1] + ImgData[ImgWidth - 2][ImgWidth - 1] + ImgData[ImgWidth - 2][ImgWidth - 2] + ImgData[1][ImgWidth - 1]) / 4 + 0.5); ImgData2[ImgHeight - 1][0] = (unsigned char)((float)(ImgData[ImgHeight - 1][0] + ImgData[ImgHeight - 1][1] + ImgData[ImgHeight - 2][0] + ImgData[ImgHeight - 2][1]) / 4 + 0.5); ImgData2[ImgHeight - 1][ImgWidth - 1] = (unsigned char)((float)(ImgData[ImgHeight - 1][ImgWidth - 1] + ImgData[ImgHeight - 2][ImgWidth - 1] + ImgData[ImgHeight - 2][ImgWidth - 2] + ImgData[ImgHeight - 1][ImgWidth - 2]) / 4 + 0.5); //图像边界的操作. for (int i = 1; i < ImgWidth - 1; i++) { //第一行. ImgData2[0][i] = (unsigned char)((float)(ImgData[0][i - 1] + ImgData[0][i] + ImgData[0][i + 1] + ImgData[1][i - 1] + ImgData[1][i] + ImgData[1][i + 1]) / 6+0.5); //最后一行. ImgData2[ImgHeight - 1][i] = (unsigned char)((float)(ImgData[ImgHeight - 2][i - 1] + ImgData[ImgHeight - 2][i] + ImgData[ImgHeight - 2][i + 1] + ImgData[ImgHeight - 1][i - 1] + ImgData[ImgHeight - 1][i] + ImgData[ImgHeight - 1][i + 1]) / 6+0.5); } for (int i = 1; i < ImgHeight - 1; i++) { //第一列. ImgData2[i][0] = (unsigned char)((float)(ImgData[i - 1][0] + ImgData[i - 1][1] + ImgData[i][0] + ImgData[i][1] + ImgData[i + 1][0] + ImgData[i + 1][1]) / 6+0.5); //最后一列. ImgData2[i][ImgWidth - 1] = (unsigned char)((float)(ImgData[i - 1][ImgWidth - 2] + ImgData[i - 1][ImgWidth - 1] + ImgData[i][ImgWidth - 2] + ImgData[i][ImgWidth - 1] + ImgData[i + 1][ImgWidth - 2] + ImgData[i + 1][ImgWidth - 1]) / 6+0.5); } //对中间的像素点进行附近9格均值滤波处理. for (int i = 1; i < ImgHeight - 1; i++) { for (int j = 1; j < ImgWidth - 1; j++) { //均值滤波. ImgData2[i][j] = (unsigned char)((float)(ImgData[i - 1][j + 1] + ImgData[i][j + 1] + ImgData[i + 1][j + 1] + ImgData[i - 1][j] + ImgData[i][j] + ImgData[i + 1][j] + ImgData[i - 1][j - 1] + ImgData[i][j - 1] + ImgData[i + 1][j - 1]) / 9+0.5); } } } //取数组中的中值. unsigned char getMidNum(unsigned char* allNum, int length) { int midIndex = length / 2 +1;//这里下标+1后效果更好. for (int i = 0; i < midIndex - 1; i++) { for (int j = 0; j < length - 1 - i; j++)// j开始等于0 { if (allNum[j] < allNum[j + 1]) { int temp = allNum[j]; allNum[j] = allNum[j + 1]; allNum[j + 1] = temp; } } } return allNum[midIndex]; } //中值滤波器. void midSmoothing(unsigned char ** ImgData, unsigned char ** ImgData2, int ImgWidth, int ImgHeight) { //这里对数组赋值有没有有效一点的方法啊 unsigned char tempData[9] = { ImgData[0][0], ImgData[0][1], ImgData[1][0], ImgData[1][1] }; //对图像的四个角点操作. ImgData2[0][0] = getMidNum(tempData, 4); tempData[0] = ImgData[0][ImgWidth - 1]; tempData[1] = ImgData[ImgWidth - 2][ImgWidth - 1]; tempData[2] = ImgData[ImgWidth - 2][ImgWidth - 2]; tempData[3] = ImgData[1][ImgWidth - 1]; ImgData2[0][ImgWidth - 1] = getMidNum(tempData, 4); tempData[0] = ImgData[ImgHeight - 1][0]; tempData[1] = ImgData[ImgHeight - 1][1]; tempData[2] = ImgData[ImgHeight - 2][0]; tempData[3] = ImgData[ImgHeight - 2][1]; ImgData2[ImgHeight - 1][0] = getMidNum(tempData, 4); tempData[0] = ImgData[ImgHeight - 1][ImgWidth - 1]; tempData[1] = ImgData[ImgHeight - 2][ImgWidth - 1]; tempData[2] = ImgData[ImgHeight - 2][ImgWidth - 2]; tempData[3] = ImgData[ImgHeight - 1][ImgWidth - 2]; ImgData2[ImgHeight - 1][ImgWidth - 1] = getMidNum(tempData, 4); //图像边界的操作. for (int i = 1; i < ImgWidth - 1; i++) { //第一行. tempData[0] = ImgData[0][i - 1]; tempData[1] = ImgData[0][i]; tempData[2] = ImgData[0][i + 1]; tempData[3] = ImgData[1][i - 1]; tempData[4] = ImgData[1][i]; tempData[5] = ImgData[1][i + 1]; ImgData2[0][i] = getMidNum(tempData, 6); //最后一行. tempData[0] = ImgData[ImgHeight - 2][i - 1]; tempData[1] = ImgData[ImgHeight - 2][i]; tempData[2] = ImgData[ImgHeight - 2][i + 1]; tempData[3] = ImgData[ImgHeight - 1][i - 1]; tempData[4] = ImgData[ImgHeight - 1][i]; tempData[5] = ImgData[ImgHeight - 1][i + 1]; ImgData2[ImgHeight - 1][i] = getMidNum(tempData, 6); } for (int i = 1; i < ImgHeight - 1; i++) { //第一列. tempData[0] = ImgData[i - 1][0]; tempData[1] = ImgData[i - 1][1]; tempData[2] = ImgData[i][0]; tempData[3] = ImgData[i][1]; tempData[