运动估计算法c语言代码,基于块的全搜索运动估计算法实现matlab代码

以下是基于块的全搜索运动估计算法的 C 语言代码实现：

#include <stdio.h>
#include <stdlib.h>
#include <math.h>

#define WIDTH 128     // 视频帧宽度
#define HEIGHT 96     // 视频帧高度
#define BLOCK_SIZE 8  // 块大小
#define SEARCH_RANGE 8 // 搜索范围

// 定义块结构体
typedef struct Block {
    int x;
    int y;
    int motion_x;
    int motion_y;
    double error;
} Block;

// 定义图像结构体
typedef struct Image {
    int **data;
    int width;
    int height;
} Image;

// 函数声明
void read_image(char *filename, Image *image);
void write_image(char *filename, Image *image);
void destroy_image(Image *image);
void get_block(Image *image, int x, int y, Block *block);
double calculate_error(Image *image, Block *block, int dx, int dy);
void search_motion_vector(Image *image, Block *block);

int main() {
    Image *image = (Image *) malloc(sizeof(Image));
    read_image("input.yuv", image);

    int num_blocks_x = image->width / BLOCK_SIZE;
    int num_blocks_y = image->height / BLOCK_SIZE;
    Block *blocks = (Block *) malloc(num_blocks_x * num_blocks_y * sizeof(Block));

    for (int i = 0; i < num_blocks_y; i++) {
        for (int j = 0; j < num_blocks_x; j++) {
            Block *block = &blocks[i * num_blocks_x + j];
            get_block(image, j * BLOCK_SIZE, i * BLOCK_SIZE, block);
            search_motion_vector(image, block);
        }
    }

    write_image("output.yuv", image);

    destroy_image(image);
    free(blocks);

    return 0;
}

// 读取 YUV 文件
void read_image(char *filename, Image *image) {
    FILE *file = fopen(filename, "rb");

    if (file == NULL) {
        printf("Error opening file.\n");
        exit(1);
    }

    image->width = WIDTH;
    image->height = HEIGHT;
    image->data = (int **) malloc(image->height * sizeof(int *));
    for (int i = 0; i < image->height; i++) {
        image->data[i] = (int *) malloc(image->width * sizeof(int));
    }

    int YUV[3];
    int row, col;
    for (row = 0; row < image->height; row++) {
        for (col = 0; col < image->width; col++) {
            fread(YUV, sizeof(int), 3, file);
            image->data[row][col] = YUV[0]; // 只读取 Y 分量
        }
    }

    fclose(file);
}

// 写入 YUV 文件
void write_image(char *filename, Image *image) {
    FILE *file = fopen(filename, "wb");

    if (file == NULL) {
        printf("Error opening file.\n");
        exit(1);
    }

    int YUV[3] = {0, 128, 128};
    int row, col;
    for (row = 0; row < image->height; row++) {
        for (col = 0; col < image->width; col++) {
            YUV[0] = image->data[row][col];
            fwrite(YUV, sizeof(int), 3, file);
        }
    }

    fclose(file);
}

// 销毁图像
void destroy_image(Image *image) {
    for (int i = 0; i < image->height; i++) {
        free(image->data[i]);
    }
    free(image->data);
}

// 获取块
void get_block(Image *image, int x, int y, Block *block) {
    block->x = x;
    block->y = y;
    block->motion_x = 0;
    block->motion_y = 0;
    block->error = 0.0;

    for (int i = 0; i < BLOCK_SIZE; i++) {
        for (int j = 0; j < BLOCK_SIZE; j++) {
            block->error += pow(image->data[y + i][x + j], 2.0);
        }
    }
}

// 计算误差
double calculate_error(Image *image, Block *block, int dx, int dy) {
    double error = 0.0;

    for (int i = 0; i < BLOCK_SIZE; i++) {
        for (int j = 0; j < BLOCK_SIZE; j++) {
            int x = block->x + j;
            int y = block->y + i;
            int x2 = x + dx;
            int y2 = y + dy;

            if (x2 >= 0 && x2 < image->width && y2 >= 0 && y2 < image->height) {
                error += pow(image->data[y][x] - image->data[y2][x2], 2.0);
            } else {
                error += pow(image->data[y][x], 2.0);
            }
        }
    }

    return error;
}

// 搜索运动矢量
void search_motion_vector(Image *image, Block *block) {
    double min_error = block->error;
    int min_dx = 0;
    int min_dy = 0;

    for (int dy = -SEARCH_RANGE; dy <= SEARCH_RANGE; dy++) {
        for (int dx = -SEARCH_RANGE; dx <= SEARCH_RANGE; dx++) {
            double error = calculate_error(image, block, dx, dy);
            if (error < min_error) {
                min_error = error;
                min_dx = dx;
                min_dy = dy;
            }
        }
    }

    block->motion_x = min_dx;
    block->motion_y = min_dy;
}

以下是基于块的全搜索运动估计算法的 Matlab 代码实现：

clear all;
close all;

% 定义常量
WIDTH = 128;      % 视频帧宽度
HEIGHT = 96;      % 视频帧高度
BLOCK_SIZE = 8;   % 块大小
SEARCH_RANGE = 8; % 搜索范围

% 读取 YUV 文件
file = fopen('input.yuv', 'rb');
data = fread(file, WIDTH * HEIGHT * 1.5, 'uint8');
fclose(file);

% 只读取 Y 分量
YUV = reshape(data, WIDTH * 1.5, HEIGHT)';
Y = YUV(:, 1:WIDTH);

% 初始化运动矢量和误差
motion_vectors = zeros(HEIGHT / BLOCK_SIZE, WIDTH / BLOCK_SIZE, 2);
errors = zeros(HEIGHT / BLOCK_SIZE, WIDTH / BLOCK_SIZE);

% 遍历所有块
for i = 1 : HEIGHT / BLOCK_SIZE
    for j = 1 : WIDTH / BLOCK_SIZE
        % 获取当前块
        x = (j - 1) * BLOCK_SIZE + 1;
        y = (i - 1) * BLOCK_SIZE + 1;
        block = Y(y : y + BLOCK_SIZE - 1, x : x + BLOCK_SIZE - 1);
        
        % 初始化最小误差和运动矢量
        min_error = inf;
        min_dx = 0;
        min_dy = 0;
        
        % 搜索运动矢量
        for dy = -SEARCH_RANGE : SEARCH_RANGE
            for dx = -SEARCH_RANGE : SEARCH_RANGE
                x2 = x + dx;
                y2 = y + dy;
                
                % 计算误差
                if x2 >= 1 && x2 + BLOCK_SIZE - 1 <= WIDTH && y2 >= 1 && y2 + BLOCK_SIZE - 1 <= HEIGHT
                    error = sum(sum((block - Y(y2 : y2 + BLOCK_SIZE - 1, x2 : x2 + BLOCK_SIZE - 1)) .^ 2));
                else
                    error = sum(sum(block .^ 2));
                end
                
                % 更新最小误差和运动矢量
                if error < min_error
                    min_error = error;
                    min_dx = dx;
                    min_dy = dy;
                end
            end
        end
        
        % 保存运动矢量和误差
        motion_vectors(i, j, 1) = min_dx;
        motion_vectors(i, j, 2) = min_dy;
        errors(i, j) = min_error;
    end
end

% 保存运动矢量和误差为二进制文件
fid = fopen('motion_vectors.bin', 'wb');
fwrite(fid, motion_vectors, 'int16');
fclose(fid);

fid = fopen('errors.bin', 'wb');
fwrite(fid, errors, 'double');
fclose(fid);

% 保存运动矢量为文本文件
dlmwrite('motion_vectors.txt', reshape(motion_vectors, HEIGHT * WIDTH / BLOCK_SIZE ^ 2, 2), 'delimiter', ' ');

% 保存误差为图像文件
figure;
imshow(errors, []);
imwrite(errors / max(errors(:)), 'errors.png');