Merge pull request #28873 from mvanhorn:osc/28429-fix-inter-nearest-exact-fp-5x

imgproc: fix INTER_NEAREST_EXACT to match Pillow (5.x retarget of #28661) #28873

## Summary

Fixes `INTER_NEAREST_EXACT` producing different results from Pillow for images with dimensions that are multiples of 64 (e.g., 128, 192).

Retargets #28661 to 5.x per core team request.

## Root cause

The old 16-bit fixed-point arithmetic (`ifx`, `ifx0`, `>> 16`) rounds differently from Pillow's pixel-center coordinate mapping. At exact pixel boundaries (e.g., y=7 with 128 to 160: `0.4 + 7*0.8 = 5.999999999999999`), Pillow's truncation drops to 5 while the old opencv formula rounds to 6.

## Changes

- `resize.cpp`: Replace `ifx/ifx0/ify/ify0` 16-bit fixed-point with an int64 arithmetic formula equivalent to `floor((i + 0.5) * src / dst)`, computed as `((int64_t)(i * 2 + 1) * src) / (dst * 2)`. This matches Pillow's pixel-center mapping exactly, is deterministic across platforms, and avoids FP rounding divergence entirely.
- `test_resize_bitexact.cpp`: Add `NearestExact_PillowCompat` covering 4 dimension pairs including the reproducer from #28429.

## Testing

- All 3 `Resize_Bitexact` tests pass (Linear8U, Nearest8U, NearestExact_PillowCompat) on this branch built against 5.x
- Verified bit-exact match to PIL output (Python 3.14, Pillow) on 49 dimension combinations including random pairs
- Built on macOS ARM64 with HAL (carotene/KleidiCV) active

Fixes #28429

modules/imgproc/misc/python/test/test_imgproc.py

@@ -4,6 +4,10 @@ from __future__ import print_function
 
 import numpy as np
 import cv2 as cv
+try:
+    from PIL import Image
+except ImportError:
+    Image = None
 
 from tests_common import NewOpenCVTests
 
@@ -28,3 +32,17 @@ class Imgproc_Tests(NewOpenCVTests):
         img_blur0 = cv.filter2D(img, cv.CV_32F, kernel*(1./9))
         img_blur1 = cv.filter2Dp(img, kernel, ddepth=cv.CV_32F, scale=1./9)
         self.assertLess(cv.norm(img_blur0 - img_blur1, cv.NORM_INF), eps)
+
+    def test_resize_pillow(self):
+        if Image is None:
+            self.skipTest("Pillow is not available")
+
+        r = np.random.randint(0, 255, size=(128, 147, 3), dtype="uint8")
+        target_size=[(128,128), (129,129), (160,160)]
+        for ts in target_size:
+
+            pil_result = np.array(Image.fromarray(r).resize(ts, Image.NEAREST))
+            ocv_result = cv.resize(r, dsize=ts, interpolation=cv.INTER_NEAREST_EXACT)
+            status = np.all(pil_result == ocv_result)
+            print(ts, status)
+            self.assertTrue(status, "resize result differs from Pillow for target size %s" % (ts,))