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Open Source Computer Vision Library
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71 lines
2.2 KiB
71 lines
2.2 KiB
4 years ago
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// This file is part of OpenCV project.
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// It is subject to the license terms in the LICENSE file found in the top-level directory
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// of this distribution and at http://opencv.org/license.html.
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#include "test_precomp.hpp"
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namespace opencv_test {
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namespace {
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double minPSNR(UMat src1, UMat src2)
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{
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std::vector<UMat> src1_channels, src2_channels;
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split(src1, src1_channels);
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split(src2, src2_channels);
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double psnr = cvtest::PSNR(src1_channels[0], src2_channels[0]);
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psnr = std::min(psnr, cvtest::PSNR(src1_channels[1], src2_channels[1]));
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return std::min(psnr, cvtest::PSNR(src1_channels[2], src2_channels[2]));
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}
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TEST(ExposureCompensate, SimilarityThreshold)
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{
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UMat source;
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imread(cvtest::TS::ptr()->get_data_path() + "stitching/s1.jpg").copyTo(source);
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UMat image1 = source.clone();
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UMat image2 = source.clone();
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// Add a big artifact
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image2(Rect(150, 150, 100, 100)).setTo(Scalar(0, 0, 255));
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UMat mask(image1.size(), CV_8U);
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mask.setTo(255);
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detail::BlocksChannelsCompensator compensator;
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compensator.setNrGainsFilteringIterations(0); // makes it more clear
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// Feed the compensator, image 1 and 2 are perfectly
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// identical, except for the red artifact in image 2
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// Apart from that artifact, there is no exposure to compensate
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compensator.setSimilarityThreshold(1);
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uchar xff = 255;
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compensator.feed(
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{{}, {}},
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{image1, image2},
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{{mask, xff}, {mask, xff}}
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);
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// Verify that the artifact in image 2 did create
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// an artifact in image1 during the exposure compensation
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UMat image1_result = image1.clone();
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compensator.apply(0, {}, image1_result, mask);
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double psnr_no_similarity_mask = minPSNR(image1, image1_result);
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EXPECT_LT(psnr_no_similarity_mask, 45);
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// Add a similarity threshold and verify that
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// the artifact in image1 is gone
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compensator.setSimilarityThreshold(0.1);
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compensator.feed(
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{{}, {}},
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{image1, image2},
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{{mask, xff}, {mask, xff}}
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);
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image1_result = image1.clone();
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compensator.apply(0, {}, image1_result, mask);
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double psnr_similarity_mask = minPSNR(image1, image1_result);
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EXPECT_GT(psnr_similarity_mask, 300);
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}
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} // namespace
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} // namespace opencv_test
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