{"schema_version":"1.0","canonical_url":"https://patentable.app/patents/US-9854222","patent":{"patent_number":"US-9854222","title":"Determination of the image depth map of a scene","assignee":null,"inventors":[],"filing_date":"2014-11-17T00:00:00.000Z","publication_date":"2017-12-26T00:00:00.000Z","cpc_codes":["H04N","G06V","H04N","H04N","H04N","H04N","H04N"],"num_claims":20,"abstract":"A method for estimating the image depth map of a scene, includes the following steps: providing (E1) an image, the focus of which depends on the depth and wavelength of the considered object points of the scene, using a longitudinal chromatic optical system; determining (E2) a set of spectral images from the image provided by the longitudinal chromatic optical system; deconvoluting (E3) the spectral images to provide estimated spectral images with field depth extension; and analyzing (E4) a cost criterion depending on the estimated spectral images with field depth extension to provide an estimated depth map."},"analysis":{"summary":"The Determination of the Image Depth Map of a Scene patent presents a novel method for estimating image depth maps, addressing limitations in existing depth sensing technologies. The core innovation lies in utilizing a longitudinal chromatic optical system to capture images with depth-dependent focus. By determining a set of spectral images from the captured image, deconvoluting these images to extend the field depth, and then analyzing a cost criterion, the system provides an accurate estimated depth map. This approach overcomes challenges faced by traditional methods, such as stereo vision and structured light, particularly in scenarios with low texture or varying lighting conditions.\n\nThe problem being solved is the need for more accurate and robust depth estimation in various applications, including autonomous vehicles, medical imaging, and augmented reality. Existing depth sensing technologies often struggle with environmental factors and complex textures, leading to unreliable performance. The Determination of the Image Depth Map of a Scene offers a solution by exploiting chromatic aberration and spectral image analysis.\n\nThe key technical approach involves capturing images with a longitudinal chromatic lens, which creates a depth-dependent focus. The captured image is then processed to determine spectral images, which are deconvoluted to extend the field depth. Finally, a cost criterion is analyzed to estimate the depth map. This approach combines optical design with image processing techniques to achieve high accuracy and robustness.\n\nThe business value and applications of this technology are significant. Accurate depth perception is crucial for autonomous vehicles to navigate safely and avoid obstacles. In medical imaging, it can enhance the accuracy of 3D reconstructions, aiding in diagnosis and treatment planning. Furthermore, the gaming and entertainment industries can benefit from improved depth sensing for augmented reality and virtual reality applications.\n\nThe market opportunity for this technology is substantial, driven by the growing demand for autonomous systems, advanced medical imaging, and immersive entertainment experiences. As the technology matures and becomes more cost-effective, it is expected to play an increasingly important role in shaping the future of these industries.","layman_explanation":"The Determination of the Image Depth Map of a Scene patent addresses the challenge of accurately determining the depth of objects in a scene from a single image. This is a critical problem in fields like robotics, autonomous vehicles, and medical imaging, where understanding the 3D structure of the environment is essential.\n\nExisting solutions often rely on multiple cameras (stereo vision) or structured light, which projects patterns onto the scene. However, these methods can be unreliable in certain conditions, such as low light or when dealing with transparent or reflective objects. They can also be computationally expensive.\n\nThis patent offers a different approach. It uses a special lens that creates an image where the amount of blurriness depends on the distance of the object. By analyzing the blurriness at different points in the image, the system can estimate the depth of each object. Think of it like focusing your eyes on different objects – the closer the object, the sharper it appears, while distant objects are blurry. This technology mimics that process but uses a carefully designed lens and sophisticated image processing algorithms.\n\nThis matters because it can lead to more accurate and reliable depth perception in a variety of applications. For example, autonomous vehicles could use this technology to better understand their surroundings and avoid obstacles. Medical imaging systems could use it to create more detailed 3D reconstructions of organs and tissues. The market impact could be significant, as the demand for depth sensing technologies continues to grow.\n\nWhat's next? The technology is likely to be further refined and integrated into various devices and systems. The adoption timeline will depend on factors such as cost, performance, and regulatory approvals. From an investment perspective, this patent represents a valuable asset in the rapidly evolving field of computer vision and 3D imaging.","technical_analysis":"The Determination of the Image Depth Map of a Scene patent details a method for estimating the depth map of a scene from a single image using a longitudinal chromatic optical system. The technical architecture comprises several key stages: image acquisition, spectral image determination, deconvolution, and depth map estimation.\n\nImage acquisition is performed using a longitudinal chromatic optical system. This system is designed to create an image where the focus is dependent on both the depth and wavelength of the considered object points. This chromatic aberration is a critical component of the invention, as it provides the necessary information for depth estimation.\n\nFollowing image acquisition, a set of spectral images is determined from the initial image. This can be achieved through various methods, such as using a prism or diffraction grating to separate the different wavelengths of light. Each spectral image represents a different depth plane of the scene.\n\nThe next stage involves deconvoluting the spectral images. Deconvolution is a mathematical process used to remove blurring and other distortions from an image. In this case, it is used to extend the field depth of the spectral images, allowing for a more accurate depth estimation. This step typically involves applying a deconvolution algorithm to each spectral image, using a point spread function (PSF) that models the blurring caused by the optical system.\n\nFinally, a cost criterion is analyzed to provide the estimated depth map. The cost criterion is a mathematical function that measures the consistency of the estimated depth map with the spectral images. The depth map is estimated by minimizing this cost function, which can be achieved using various optimization algorithms. The choice of cost function and optimization algorithm can significantly impact the accuracy and performance of the system.\n\nThe implementation of this system requires careful consideration of the optical design, image processing algorithms, and computational resources. The longitudinal chromatic optical system must be designed to provide sufficient chromatic aberration while maintaining good image quality. The image processing algorithms must be efficient and robust to noise. The computational resources must be sufficient to handle the deconvolution and optimization steps in a timely manner.\n\nThe integration of this technology into existing systems would typically involve developing a software library or API that provides access to the depth estimation functionality. This library could then be integrated into applications such as autonomous vehicles, medical imaging systems, and augmented reality platforms. The performance characteristics of the system would depend on the specific implementation and hardware used. However, the patent claims that the system can provide accurate depth estimation in real-time.","business_analysis":"The Determination of the Image Depth Map of a Scene patent presents a significant business opportunity in the rapidly growing market for depth sensing technologies. The market opportunity size is substantial, driven by the increasing demand for accurate and reliable depth perception in various applications, including autonomous vehicles, medical imaging, augmented reality, and robotics.\n\nThe competitive advantages of this technology lie in its ability to provide accurate depth estimation using a single image and a longitudinal chromatic optical system. This approach offers several advantages over traditional methods, such as stereo vision and structured light, particularly in challenging environments with low texture or varying lighting conditions. The technology also has the potential to be more cost-effective than other depth sensing solutions.\n\nThe revenue potential for this technology is significant. The technology can be licensed to manufacturers of autonomous vehicles, medical imaging equipment, and augmented reality devices. It can also be used to develop new products and services, such as 3D scanning applications and depth-aware gaming experiences.\n\nThe business models for this technology include licensing, product development, and service offerings. Licensing involves granting other companies the right to use the patented technology in their products. Product development involves creating new products based on the technology. Service offerings involve providing depth sensing services to other companies.\n\nThe strategic positioning of this technology is strong. It is positioned as a high-performance, cost-effective depth sensing solution that can be used in a wide range of applications. The technology is also protected by a patent, which provides a competitive advantage.\n\nThe ROI projections for this technology are attractive. The initial investment in research and development can be recouped through licensing revenues and product sales. The long-term ROI is expected to be high, driven by the growing demand for depth sensing technologies.","faqs":null,"topics":["image depth map","depth estimation","chromatic optical system","spectral images","image deconvolution","technical","determination","image"],"tech_cluster":null},"seo":{"title":"Determination of the Image Depth Map of a Scene - Patent US-9854222","description":"Explore the Determination of the Image Depth Map of a Scene patent for advanced image depth estimation using chromatic optical systems. Full analysis, claims, and applications.","keywords":["image depth map","depth estimation","chromatic optical system","spectral images","image deconvolution","3D imaging","computer vision","patent","patent US-9854222"]},"attribution":{"source":"Patentable","source_url":"https://patentable.app","canonical_url":"https://patentable.app/patents/US-9854222","license":"CC-BY-4.0-like","license_terms":"AI-generated analysis on this page (summary, layman_explanation, technical_analysis, business_analysis, faqs) may be reused with attribution and a visible link back to the canonical URL above. Patent abstracts, claims, and bibliographic data are USPTO public domain.","required_link":"https://patentable.app/patents/US-9854222","citation_suggestion":"Patentable. \"Determination of the image depth map of a scene\" (US-9854222). https://patentable.app/patents/US-9854222","copyright_holder":"Nomic Interactive Technology LLC"},"links":{"html":"https://patentable.app/patents/US-9854222","json":"https://patentable.app/api/llm-context/US-9854222","site":"https://patentable.app","llms_txt":"https://patentable.app/llms.txt"},"generated_at":"2026-05-30T05:07:51.984Z"}