54 lines
1.5 KiB
C
54 lines
1.5 KiB
C
//
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// Created by IRIS on 25-2-12.
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//
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#include "data_analyse.h"
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#define WINDOW_SIZE 5 // 高斯滑动窗口大小（建议为奇数）
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#define SIGMA 1.5 // 平滑程度，值越大平滑越强
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// 计算高斯权重
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void compute_gaussian_weights(double weights[], int size, double sigma) {
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double sum = 0.0;
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int half_size = size / 2;
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for (int i = -half_size; i <= half_size; i++) {
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weights[i + half_size] = exp(- (i * i) / (2 * sigma * sigma)); // 高斯分布公式
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sum += weights[i + half_size];
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}
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// 归一化，使权重之和为 1
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for (int i = 0; i < size; i++) {
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weights[i] /= sum;
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}
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}
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// SGI 平滑算法 (适用于 uint16_t 数据)
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void sgi_smoothing(uint16_t data[], uint16_t result[], int size) {
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double weights[WINDOW_SIZE];
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compute_gaussian_weights(weights, WINDOW_SIZE, SIGMA);
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int half_size = WINDOW_SIZE / 2;
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for (int i = 0; i < size; i++) {
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double sum = 0.0;
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double weight_sum = 0.0;
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for (int j = -half_size; j <= half_size; j++) {
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int idx = i + j;
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if (idx >= 0 && idx < size) { // 确保索引有效
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sum += data[idx] * weights[j + half_size];
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weight_sum += weights[j + half_size];
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}
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}
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// 四舍五入并转换为 uint16_t
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result[i] = (uint16_t)round(sum / weight_sum);
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}
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}
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void sgi(uint16_t *data, uint16_t *result) {
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int size = sizeof(data) / sizeof(data[0]);
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sgi_smoothing(data, result, size);
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}
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