C++图像处理器 滤镜特效开发

struct Pixel {
    unsigned char r, g, b;
};

std::vector> image; // 二维
// 或
std::vector imageData; // 一维，宽×高

#define STB_IMAGE_IMPLEMENTATION
#include "stb_image.h"
#define STB_IMAGE_WRITE_IMPLEMENTATION
#include "stb_image_write.h"

for (auto& pixel : imageData) {
    float gray = 0.299f * pixel.r + 0.587f * pixel.g + 0.114f * pixel.b;
    pixel.r = pixel.g = pixel.b = static_cast(gray);
}

for (auto& pixel : imageData) {
    pixel.r = 255 - pixel.r;
    pixel.g = 255 - pixel.g;
    pixel.b = 255 - pixel.b;
}

int brightness = 50; // 正值变亮，负值变暗
for (auto& pixel : imageData) {
    pixel.r = std::clamp(pixel.r + brightness, 0, 255);
    pixel.g = std::clamp(pixel.g + brightness, 0, 255);
    pixel.b = std::clamp(pixel.b + brightness, 0, 255);
}

float contrast = 1.5f; // >1增强，<1减弱
for (auto& pixel : imageData) {
    pixel.r = std::clamp(128 + contrast * (pixel.r - 128), 0.0f, 255.0f);
    pixel.g = std::clamp(128 + contrast * (pixel.g - 128), 0.0f, 255.0f);
    pixel.b = std::clamp(128 + contrast * (pixel.b - 128), 0.0f, 255.0f);
}

int kernelSize = 3;
int radius = kernelSize / 2;
std::vector output = imageData;
for (int y = radius; y < height - radius; ++y) {
for (int x = radius; x < width - radius; ++x) {
int sumR = 0, sumG = 0, sumB = 0;
for (int ky = -radius; ky <= radius; ++ky) {
for (int kx = -radius; kx <= radius; ++kx) {
int idx = (y + ky)  width + (x + kx);
sumR += imageData[idx].r;
sumG += imageData[idx].g;
sumB += imageData[idx].b;
}
}
int count = kernelSize  kernelSize;
int idx = y * width + x;
output[idx].r = sumR / count;
output[idx].g = sumG / count;
output[idx].b = sumB / count;
}
}
imageData = std::move(output);

class Filter {
public:
    virtual void apply(std::vector& data, int width, int height) = 0;
    virtual ~Filter() = default;
};
class GrayscaleFilter : public Filter {
public:
void apply(std::vector& data, int, int) override {
for (auto& p : data) {
// 灰度转换逻辑
}
}
};