core: SIMD optimizations for norm, distance and Hamming APIs. (Improves ORB & BRISK) #29335
Generic universal-intrinsic kernels (benefit all SIMD backends: NEON, AVX2, AVX-512, etc.), plus enabling wider dispatch for the norm module.
- hal::normHamming: cached-pointer dispatch (resolve once, no per-call dispatch chain or trace region) + vector popcount path. cv::norm(NORM_HAMMING) and binary-descriptor matching (BFMatcher ORB/BRISK/FREAK via cv::batchDistance).
- hal::normL2Sqr_ / normL1_: direct inlinable kernels with single-vector tail (cv::batchDistance / BFMatcher float L2/L1, cv::kmeans).
- cv::norm masked NORM_INF: deinterleave SIMD for multichannel + back-step tail.
- cv::norm(src1, src2, type, mask): SIMD masked norm-diff; INF is one templated kernel for all element types, plus uchar L1/L2 and int L1 kernels.
- Enable AVX512_SKX/AVX512_ICL dispatch for the norm module.
- features2d: add BFMatcher knnMatch perf tests (float L2/L1, binary Hamming).
- ORB and BRISK performance improved
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More use of AutoBuffer #28907
When possible, AutoBuffer should be faster than std::vector<>, and should not be worse if it requires a heap allocation rather than a stack allocation.
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Feat: Add OpenCL support for AKAZE features #28879
Implement OpenCL-accelerated AKAZE feature
detection and descriptor extraction
Benchmarked on RTX 5060 Ti: 1.2x to 3.31x faster
for image sizes from 640x480 to 3840x2160
- Added 8 OpenCL kernels for feature detection and descriptor extraction
- Refactored compute_kcontrast to use OpenCV magnitude() for consistency
- Added comprehensive tests with >95% accuracy vs CPU baseline
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The existing 2-pass cross-check implementation requires both forward and
reverse distance computations on GPU, followed by CPU-side filtering.
This adds a single-pass kernel using int64 atomics to eliminate the
reverse pass. The BruteForceMatch_CrossCheckMatch kernel performs forward
matching and tracks best train->query mappings in one GPU pass, reducing
memory transfers. Falls back to 2-pass approach on devices without
cl_khr_int64_base_atomics extension.
Tested on NVIDIA RTX 5060 Ti: 1.65x-1.97x faster than 2-pass GPU,
3.49x-7.33x faster than CPU at 640x480 to 1920x1080 resolutions.
BFMatcher::match() with crossCheck=true previously skipped the OCL
dispatch in knnMatchImpl entirely, falling back to CPU even when UMat
inputs and an OpenCL device were available. This adds
ocl_matchWithCrossCheck() for CV_32FC1 descriptors (e.g. SIFT, SURF):
both the forward and reverse nearest-neighbour passes run on the GPU
via the existing ocl_matchSingle() kernel, then the cross-check filter
runs on the CPU. Only two small index arrays (1×N ints) are downloaded
— the O(N²×D) distance work stays on the device.
The OCL dispatch in knnMatchImpl is also refactored to unify the
Mat/UMat train collection selection before branching on crossCheck.
On a NVIDIA RTX 3060 with SIFT descriptors the OCL path is 6–9×
faster than CPU at 2k–10k features per image. Binary descriptors
(ORB, BRIEF — CV_8U) are unaffected; the existing type guard in
ocl_matchSingle keeps them on the CPU path as before.
Also adds a correctness test (Features2d_BFMatcher_CrossCheck) and an
OCL perf test (BruteForceMatcherFixture/MatchCrossCheck).
features2d: add missing KAZE DIFF_CHARBONNIER support #28324
### Description
This PR fixes the missing implementation for `DIFF_CHARBONNIER` diffusivity type in KAZE feature detector.
### Changes
- Added `charbonnier_diffusivity()` call for `DIFF_CHARBONNIER` type in `Create_Nonlinear_Scale_Space()`
- Added proper error handling for unsupported diffusivity types
### Problem
When using KAZE with `DIFF_CHARBONNIER` diffusivity type, keypoint coordinates were not computed at subpixel level, because the code lacked the specific handling for this diffusivity mode.
### Solution
The `charbonnier_diffusivity()` function already exists in `nldiffusion_functions.cpp`, it just wasn't being called. This PR adds the missing `else if` branch to call it, matching the pattern already implemented in `AKAZEFeatures.cpp`.
Fixes#27134
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docs: fix spelling errors in documentation and code #28301
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### Description
Fixed multiple spelling errors across documentation, comments, and code:
- 'colummn' → 'column' (cublas.hpp, 3 occurrences)
- 'points_per_colum' → 'points_per_column' (calib3d.hpp, 3 occurrences)
- 'Asignee' → 'Assignee' (sift files, 2 occurrences)
- 'compability' → 'compatibility' (face.hpp, 2 occurrences)
- 'orignal' → 'original' (aruco_detector.cpp)
- 'refrence' → 'reference' (chessboard.cpp)
- 'indeces' → 'indices' (stitching.hpp)
- 'OutputPrecison' → 'OutputPrecision' (test)
- 'tranform' → 'transform' (slice_layer.cpp, 3 occurrences)
Total: 24 fixes across 14 files. Documentation and comment changes only, no functional impact.
Properly preserve KAZE/AKAZE license as mandated by BSD-3-Clause #28441
Close https://github.com/opencv/opencv/issues/28440
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docs(features2d): document getBlobContours and collectContours in SimpleBlobDetector #28275
Description: This PR adds missing Doxygen documentation for the getBlobContours() method and the collectContours parameter in SimpleBlobDetector. These features were previously undocumented, making the contour collection functionality difficult for users to discover and use correctly.
Changes:
Added a @brief and detailed note for SimpleBlobDetector::Params::collectContours.
Added documentation for SimpleBlobDetector::getBlobContours(), including a @note regarding the required parameter setup.
Testing:
Verified the documentation build locally on macOS using ninja opencv_docs.
Confirmed the generated HTML displays the descriptions and cross-references accurately.
Partially fixes: #25904
Related PR that adds method: https://github.com/opencv/opencv/pull/21942
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Fix ORB inconsistency for masks with values 255 and 1. #26366
### Pull Request Readiness Checklist
The PR fixes : [25974](https://github.com/opencv/opencv/issues/25974)
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The pointer offset to move from top-right to bottom-right was incorrect. This change corrects the pointer calculation to use the proper row stride, ensuring it lands on the correct pixel.
stitching: enable loop unrolling in fast.cpp to improve ARM64 performance #27642
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- This PR introduces an ARM64-specific performance optimization in the FAST_t function by applying loop unrolling.
- The optimization is guarded with #if defined(_M_ARM64) to ensure it only affects ARM64 builds.
- This optimizations lead to performance improvements in stitching module functions.
**Performance Improvements:**
- This change significantly improved the performance on Windows ARM64 targets.
<img width="935" height="579" alt="image" src="https://github.com/user-attachments/assets/a03833d1-ac9b-408f-916b-243fd6ae2d53" />
features2d: performance optimization of detect function on Windows-ARM64 #27776
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- This PR improves the performance of the detect function on Windows ARM64 targets.
- Added the defined(_M_ARM64) macro in agast.cpp and agast_score.cpp files, aligning ARM64 behavior with how x64 selects internal functions for computation.
- As a result, ARM64 now executes the same internal functions as x64 where applicable, leading to measurable performance improvements in detect function.
- This changes is limited to Windows ARM64 and does not affect other architectures
**Performance impact:**
- Detect function shows improved runtime on ARM64 targets due to reuse of existing efficient computation paths.
<img width="1419" height="408" alt="image" src="https://github.com/user-attachments/assets/feab411a-d256-4bff-bec2-22b2583f63d1" />
Support C++20 standard #26590
Close https://github.com/opencv/opencv/issues/26589
Related https://github.com/opencv/opencv_contrib/pull/3842
Related: https://github.com/opencv/opencv/issues/20269
- do not arithmetic enums and ( different enums or floating numeric)
- remove unused variable
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Replace operators with wrapper functions on universal intrinsics backends #26109
This PR aims to replace the operators(logic, arithmetic, bit) with wrapper functions(v_add, v_eq, v_and...)
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Imgproc: use double to determine whether the corners points are within src #26022close#26016
Related https://github.com/opencv/opencv_contrib/pull/3778
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Split Javascript white-list to support contrib modules #25986
Single whitelist converted to several per-module json files. They are concatenated automatically and can be overriden by user config.
Related to https://github.com/opencv/opencv/pull/25656
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core: persistence: output reals as human-friendly expression. #25351Close#25073
Related https://github.com/opencv/opencv/pull/25087
This patch is need to merge same time with https://github.com/opencv/opencv_contrib/pull/3714
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Documentation transition to fresh Doxygen #25042
* current Doxygen version is 1.10, but we will use 1.9.8 for now due to issue with snippets (https://github.com/doxygen/doxygen/pull/10584)
* Doxyfile adapted to new version
* MathJax updated to 3.x
* `@relates` instructions removed temporarily due to issue in Doxygen (to avoid warnings)
* refactored matx.hpp - extracted matx.inl.hpp
* opencv_contrib - https://github.com/opencv/opencv_contrib/pull/3638
Rewrite Universal Intrinsic code: features2d and calib3d module. #24301
The goal of this series of PRs is to modify the SIMD code blocks guarded by CV_SIMD macro: rewrite them by using the new Universal Intrinsic API.
This is the modification to the features2d module and calib3d module.
Test with clang 16 and QEMU v7.0.0. `AP3P.ctheta1p_nan_23607` failed beacuse of a small calculation error. But this patch does not touch the relevant code, and this error always reproduce on QEMU, regardless of whether the patch is applied or not. I think we can ignore it
```
[ RUN ] AP3P.ctheta1p_nan_23607
/home/hanliutong/project/opencv/modules/calib3d/test/test_solvepnp_ransac.cpp:2319: Failure
Expected: (cvtest::norm(res.colRange(0, 2), expected, NORM_INF)) <= (3e-16), actual: 3.33067e-16 vs 3e-16
[ FAILED ] AP3P.ctheta1p_nan_23607 (26 ms)
...
[==========] 148 tests from 64 test cases ran. (1147114 ms total)
[ PASSED ] 147 tests.
[ FAILED ] 1 test, listed below:
[ FAILED ] AP3P.ctheta1p_nan_23607
```
Note: There are 2 test cases failed with GCC 13.2.1 without this patch, seems like there are someting wrong with RVV part on GCC.
```
[----------] Global test environment tear-down
[==========] 148 tests from 64 test cases ran. (1511399 ms total)
[ PASSED ] 146 tests.
[ FAILED ] 2 tests, listed below:
[ FAILED ] Calib3d_StereoSGBM.regression
[ FAILED ] Calib3d_StereoSGBM_HH4.regression
```
The patch is partially auto-generated by using the [rewriter](https://github.com/hanliutong/rewriter).
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Properly preserve chi_table license as mandated by BSD-3-Clause #24204
Amend reference to online hosted file with the full license quotation as mandated by the original license.
* different interpolation by double image
* fixing scaling mapping
* fixing a test
* added an option to enable previous interpolation
* added doxygen entries for the new parameter
* ASSERT_TRUE -> ASSERT_EQ
* changed log message when using old upscale mode
Uwez Khan
Madan mohan Manokar
Pierre Chatelier
Yixuan Tang
Primary-H
Anand Mahesh
Kumataro
Murat Raimbekov
Alexander Smorkalov
Vincent Rabaud
Shruti Arsode
Skreg
Haodi Yao
pratham-mcw
Alexander Smorkalov
Haosonn
utibenkei
Maksim Shabunin
Wanli
Alexander Lyulkov
Alexander Smorkalov
Liutong HAN
Sean McBride
Yuriy Chernyshov
Vadim Pisarevsky
Vaclav Vavra
Alexander Alekhin