OV9281: 1MP OmniPixel 3-GS黑白CMOS图像传感器规格预览

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OV9281-Preliminary-Specification-CSP5-Version-1-1_Omnivision.pdf 是一份关于OmniVision公司生产的1/4英寸黑白CMOS一千万像素(1280x800)图像传感器的初步规格说明书。这款传感器采用了先进的OmniPixel3-GS™技术,旨在提供高分辨率和高效能的图像采集解决方案。 该文档的核心内容概述了OV9281传感器的关键特性: 1. 图像传感器类型:它是一款CMOS(Complementary Metal-Oxide-Semiconductor)传感器,这使得它在功耗管理和集成度方面具有优势。 2. 分辨率:1280x800像素的分辨率提供了清晰的成像效果,适用于各种需要高质量图像的应用场景,如安防监控、手机摄像头或工业自动化等。 3. OmniPixel3-GS™技术:这项技术可能是指OmniVision自家的像素级处理技术,可能包括先进的图像信号处理算法、降噪功能、色彩增强等,以提升传感器的性能和图像质量。 4. 版权与使用条款:文档明确指出,此文件仅供OmniVision内部使用,并且所有权利归OmniVision Technologies, Inc.所有。它没有提供任何形式的保证,包括但不限于商品质量、非侵权性、特定用途适用性等,而且没有授予任何知识产权许可,用户必须获得公司的授权才能使用这份技术信息。 5. 责任声明:OmniVision Technologies及其关联公司对使用文档中的信息承担有限责任,特别是关于侵犯专利权的责任,并且声明没有默示或明示地授予任何知识产权许可。 6. 保密性:由于标记为“proprietary”,这意味着这份规格说明书中的信息是专有的,仅限于被授权的个人或组织使用,不得随意传播。 OV9281-Preliminary-Specification-CSP5-Version-1-1_Omnivision.pdf主要提供了一款高性能图像传感器的技术细节,对于那些寻求利用这款传感器进行产品设计或了解其性能特点的专业人士来说,它是宝贵的信息来源。在实际应用中,开发者需要遵守文档中提到的所有使用限制和责任声明,以确保合规性和尊重知识产权。

解释:% 'Distance' - Distance measure, in P-dimensional space, that KMEANS % should minimize with respect to. Choices are: % {'sqEuclidean'} - Squared Euclidean distance (the default) % 'cosine' - One minus the cosine of the included angle % between points (treated as vectors). Each % row of X SHOULD be normalized to unit. If % the intial center matrix is provided, it % SHOULD also be normalized. % % 'Start' - Method used to choose initial cluster centroid positions, % sometimes known as "seeds". Choices are: % {'sample'} - Select K observations from X at random (the default) % 'cluster' - Perform preliminary clustering phase on random 10% % subsample of X. This preliminary phase is itself % initialized using 'sample'. An additional parameter % clusterMaxIter can be used to control the maximum % number of iterations in each preliminary clustering % problem. % matrix - A K-by-P matrix of starting locations; or a K-by-1 % indicate vector indicating which K points in X % should be used as the initial center. In this case, % you can pass in [] for K, and KMEANS infers K from % the first dimension of the matrix. % % 'MaxIter' - Maximum number of iterations allowed. Default is 100. % % 'Replicates' - Number of times to repeat the clustering, each with a % new set of initial centroids. Default is 1. If the % initial centroids are provided, the replicate will be % automatically set to be 1. % % 'clusterMaxIter' - Only useful when 'Start' is 'cluster'. Maximum number % of iterations of the preliminary clustering phase. % Default is 10. %

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