uri参数

https://api.flickr.com/services/rest/
private static final String ENDPOINT = "https://api.flickr.com/services/rest/";

private static final String KEY_METHOD = "method";
private static final String KEY_API_KEY = "api_key";
private static final String KEY_FORMAT = "format";
private static final String KEY_NO_JSON_CALLBACK = "nojsoncallback";
private static final String KEY_PARAM_EXTRAS = "extras";
private static final String KEY_PARAM_TEXT = "text";

private static final String VALUE_METHOD_GET_RECENT = "flickr.photos.getRecent";
private static final String VALUE_METHOD_SEARCH = "flickr.photos.search";
private static final String VALUE_FORMAT_JSON = "json";
private static final String VALUE_PARAM_EXTRA_SMALL_URL = "url_s";

private static final int ID_API_KEY = R.string.api_key;

/**
https://api.flickr.com/services/rest/?
method=flickr.photos.getRecent
&api_key=xxx
&format=json
&nojsoncalllback=1
*/


String url = Uri.parse(ENDPOINT).buildUpon() .appendQueryParameter(KEY_METHOD, VALUE_METHOD_GET_RECENT) .appendQueryParameter(KEY_API_KEY, api_key) .appendQueryParameter(KEY_FORMAT, VALUE_FORMAT_JSON) .appendQueryParameter(KEY_NO_JSON_CALLBACK, "1") .appendQueryParameter(KEY_PARAM_EXTRAS, VALUE_PARAM_EXTRA_SMALL_URL) .build().toString();
以下是彩色图像的PSNRSSIMLPIPS和CIEDE2000评价算法的Matlab源码示例: 1. PSNR(峰值信噪比): ```matlab function psnr_value = PSNR(original, distorted) [M, N, ~] = size(original); mse = sum((original(:) - distorted(:)).^2) / (M * N * 3); max_value = max(original(:)); psnr_value = 10 * log10(max_value^2 / mse); end ``` 2. SSIM(结构相似性指数): ```matlab function ssim_value = SSIM(original, distorted) K1 = 0.01; K2 = 0.03; L = 255; C1 = (K1 * L)^2; C2 = (K2 * L)^2; original = double(original); distorted = double(distorted); mean_original = filter2(fspecial('gaussian', 11, 1.5), original, 'valid'); mean_distorted = filter2(fspecial('gaussian', 11, 1.5), distorted, 'valid'); var_original = filter2(fspecial('gaussian', 11, 1.5), original.^2, 'valid') - mean_original.^2; var_distorted = filter2(fspecial('gaussian', 11, 1.5), distorted.^2, 'valid') - mean_distorted.^2; cov_original_distorted = filter2(fspecial('gaussian', 11, 1.5), original .* distorted, 'valid') - mean_original .* mean_distorted; ssim_map = ((2 * mean_original .* mean_distorted + C1) .* (2 * cov_original_distorted + C2)) ./ ((mean_original.^2 + mean_distorted.^2 + C1) .* (var_original + var_distorted + C2)); ssim_value = mean2(ssim_map); end ``` 3. LPIPS(感知相似性指标):需要下载并使用LPIPS库,源码和使用说明可在https://github.com/richzhang/PerceptualSimilarity 找到。 4. CIEDE2000(CIE 2000色差公式):需要下载并使用CIEDE2000库,源码和使用说明可在https://www.mathworks.com/matlabcentral/fileexchange/46861-color-difference-cie-de2000 找到。 以上是基本的示例代码,用于评估图像质量的不同评价指标。你可以根据实际需求和图像数据进行适当的调整和修改。
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值