विधियों की तुलना करें

	स्टीरियो मैचिंग	हिस्टोग्राम इक्वलाइजेशन
क्षेत्र	कंप्यूटर दृष्टि	कंप्यूटर दृष्टि
परिवार	Machine learning	Machine learning
उद्भव वर्ष	1990s	1970s
प्रवर्तक	David Scharstein and Richard Szeliski	Signal processing community
प्रकार	Depth estimation and 3D vision	Contrast enhancement and preprocessing
मौलिक स्रोत	Scharstein, D., & Szeliski, R. (2002). A taxonomy and evaluation of dense two-frame stereo correspondence algorithms. International Journal of Computer Vision, 47(1), 7–42.	Gonzalez, R. C., & Woods, R. E. (1992). Digital Image Processing. Addison-Wesley, 2nd edition, Chapter 3.
उपनाम	Stereo correspondence, Disparity estimation	Histogram stretching, Contrast enhancement
संबंधित	5	5
सारांश	Stereo matching is a computer vision technique for recovering depth information by finding corresponding points between a pair of stereo images (taken from slightly different viewpoints). By locating the same scene feature in both images and measuring the disparity (horizontal shift), stereo matching reconstructs 3D structure using the principles of triangulation.	Histogram equalization is an image preprocessing technique that redistributes pixel intensities to improve contrast and visibility of details. By spreading the histogram of pixel values evenly across the available range, histogram equalization enhances images with poor contrast, making features more visually distinct and easier to process algorithmically.