原理：

　　離散餘弦變換(DCT for Discrete Cosine Transform)是與傅立葉變換相關的一種變換，它類似於離散傅立葉變換(DFT for Discrete Fourier Transform),但是隻使用實數。離散餘弦變換相當於一個長度大概是它兩倍的離散傅立葉變換，這個離散傅立葉變換是對一個實偶函式進行的（因為一個實偶函式的傅立葉變換仍然是一個實偶函式），在有些變形裡面需要將輸入或者輸出的位置移動半個單位(DCT有8種標準型別，其中4種是常見的)。

　　使用場景：

　　離散餘弦變換，尤其是它的第二種型別，經常被訊號處理和影象處理使用，用於對訊號和影象(包括靜止影象和運動影象)進行

　　python原始碼實現：

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

void dct(float **DCTMatrix, float **Matrix, int N, int M);
void write_mat(FILE *fp, float **testRes, int N, int M);
 
void idct(float **Matrix, float **DCTMatrix, int N, int M);
float **calloc_mat(int dimX, int dimY);
void free_mat(float **p);


float **calloc_mat(int dimX, int dimY){
    float **m = calloc(dimX, sizeof(float*));
    float *p = calloc(dimX*dimY, sizeof(float));
    int i;
    for(i=0; i <dimX;i++){
        m[i] 
 
= &p[i*dimY];

    }
    return m;
}

void free_mat(float **m){
    free(m[0]);
    free(m);
}

void write_mat(FILE *fp, float **m, int N, int M){

    int i, j;
    for(i =0; i< N; i++){
        fprintf(fp, "%f", m[i][0]);
        for(j = 1; j < M; j++){
            fprintf(fp, "\t%f", m[i][j]);
        }
        fprintf(fp, "\n");
    }
    fprintf(fp, "\n");
}

void dct(float **DCTMatrix, float **Matrix, int N, int M){

    int i, j, u, v;
    for (u = 0; u < N; ++u) {
        for (v = 0; v < M; ++v) {
            DCTMatrix[u][v] = 0;
            for (i = 0; i < N; i++) {
                for (j = 0; j < M; j++) {
                    DCTMatrix[u][v] += Matrix[i][j] * cos(M_PI/((float)N)*(i+1./2.)*u)*cos(M_PI/((float)M)*(j+1./2.)*v);
                }
            }
        }
    }
}

void idct(float **Matrix, float **DCTMatrix, int N, int M){
    int i, j, u, v;

    for (u = 0; u < N; ++u) {
        for (v = 0; v < M; ++v) {
            Matrix[u][v] = 1/4.*DCTMatrix[0][0];
            for(i = 1; i < N; i++){
                Matrix[u][v] += 1/2.*DCTMatrix[i][0];
            }
            for(j = 1; j < M; j++){
                Matrix[u][v] += 1/2.*DCTMatrix[0][j];
            }

            for (i = 1; i < N; i++) {
                for (j = 1; j < M; j++) {
                    Matrix[u][v] += DCTMatrix[i][j] * cos(M_PI/((float)N)*(u+1./2.)*i)*cos(M_PI/((float)M)*(v+1./2.)*j);
                }                
            }
            Matrix[u][v] *= 2./((float)N)*2./((float)M);
        }
    }
}
    


int main() {
    
    float   
        testBlockA[8][8] = { {255, 255, 255, 255, 255, 255, 255, 255},
            {255, 255, 255, 255, 255, 255, 255, 255},
            {255, 255, 255, 255, 255, 255, 255, 255},
            {255, 255, 255, 255, 255, 255, 255, 255},
            {255, 255, 255, 255, 255, 255, 255, 255},
            {255, 255, 255, 255, 255, 255, 255, 255},
            {255, 255, 255, 255, 255, 255, 255, 255},
            {255, 255, 255, 255, 255, 255, 255, 255} },

        testBlockB[8][8] = {{255, 0, 255, 0, 255, 0, 255, 0},
            {0, 255, 0, 255, 0, 255, 0, 255},
            {255, 0, 255, 0, 255, 0, 255, 0},
            {0, 255, 0, 255, 0, 255, 0, 255},
            {255, 0, 255, 0, 255, 0, 255, 0},
            {0, 255, 0, 255, 0, 255, 0, 255},
            {255, 0, 255, 0, 255, 0, 255, 0},
            {0, 255, 0, 255, 0, 255, 0, 255} };

    FILE * fp = fopen("mydata.csv", "w");
    int dimX = 8, dimY = 8;
    int i, j;

    float **testBlock = calloc_mat(dimX, dimY);
    float **testDCT = calloc_mat(dimX, dimY);
    float **testiDCT = calloc_mat(dimX, dimY);
    
    for(i = 0; i<dimX; i++){
        for(j = 0; j<dimY; j++){
            testBlock[i][j] = testBlockB[i][j];
        }
    }
    
    dct(testDCT, testBlock, dimX, dimY);
    write_mat(fp, testDCT, dimX, dimY);

    idct(testiDCT, testDCT, dimX, dimY);
    write_mat(fp, testiDCT, dimX, dimY);

    fclose(fp);
    free_mat(testBlock);
    free_mat(testDCT);
    free_mat(testiDCT);

    return 0;
}

　　程式碼路徑: https://github.com/DyLanCao/DCT.git

參考文件:

1 https://stackoverflow.com/questions/8310749/discrete-cosine-transform-dct-implementation-c