What is the history and development of bicubic interpolation?
Best insight from top research papers
Bicubic interpolation has a rich history and development trajectory. Initially, bicubic interpolation was proposed as a method to compensate for the limited resolution of pixelated detectors in diffraction-limited holographic imaging . Over time, the concept evolved, leading to the introduction of the piecewise planar method (PPM) for constructing basic functions, which included bicubic interpolation as a key example . Further advancements included the implementation of fast fixed-point algorithms on FPGA for efficient bicubic interpolation in image processing systems, achieving significant energy savings and high calculation speeds . Real-time image processing systems widely adopted bicubic interpolation due to its quality, prompting the development of algorithms that combine linear and cubic interpolations to reduce hardware resource consumption while maintaining interpolation quality . Additionally, new algorithms have been introduced to compute interpolating spline surfaces over non-uniform grids with improved computational efficiency .
Answers from top 5 papers
More filters
| Papers (5) | Insight |
|---|---|
| The paper introduces a new algorithm for bicubic spline interpolation, enhancing the classic de Boor's method by reducing equation systems and explicit formulas, achieving up to 50% speedup. | |
21 Nov 2019 4 Citations | Bicubic interpolation evolved as a computationally complex but high-quality method for image scaling, surpassing nearest neighbor and bilinear methods. The paper focuses on a fast fixed-point FPGA implementation for efficiency. |
5 Citations | Not addressed in the paper. |
26 Apr 2020 2 Citations | The piecewise planar method (PPM) for bicubic interpolation evolved from Courant's linear bases idea, enabling efficient construction of higher-order triangular finite elements with special zero level lines. |
22 Jun 2020 | Not addressed in the paper. |
Related Questions
Who was the first to work on the birimian?4 answersMarat Abzalov was the first to propose the localized uniform conditioning (LUC) technique for the Birimian-style gold deposit. The Birimian of the West African Craton, known for its mafic magmatism and hosting significant mineral deposits like gold, remains a subject of differing opinions among researchers. The Birimian rocks in the Kedougou-Kenieba-Inlier of Eastern Senegal have been extensively analyzed for their geochemical and isotopic compositions, revealing a juvenile character and shedding light on the complex evolution of the Birimian Supergroups in the West African Craton. The Birimian event, which occurred during the Siderian to Orosirian period, led to the establishment of the crystalline basement of the West African Craton through the accretion of juvenile crust, with the Birimian crust experiencing multiple tectonothermal events and intrusive activities.
What is the history and evolution of fuzzy logic?5 answersFuzzy logic, introduced by Dr. Lotfi Zadeh in the 1960s, stemmed from the need to handle the ambiguity inherent in natural language and other real-world phenomena. It extends Boolean logic by incorporating the concept of degrees of truth through fuzzy sets, allowing for flexibility in reasoning and accommodating imprecision and uncertainties. Initially met with skepticism, fuzzy logic has gained widespread acceptance over the years, finding applications in control systems, artificial intelligence, and decision-making processes. This evolution from philosophical origins to practical implementation has led to the utilization of fuzzy set theories like Basic Fuzzy Logic and T-Norm Fuzzy logics in modern computer systems, showcasing the continuous development and relevance of fuzzy logic in various fields.
What is the History of AI?5 answersThe history of Artificial Intelligence (AI) spans nearly a century, evolving through various stages of development. Initially rooted in the grand European philosophical tradition, AI research gained momentum during the Cold War era, with a focus on the relationship between reason, logic, intelligence, and cognition. Over time, AI progressed from rules to statistics to data-driven methods in fields like computer vision, natural language processing, and machine learning. The history of modern AI, from 1940 to 2021, encompasses significant milestones in hardware, software, algorithms, and technologies. Notably, modern AI is characterized by the dominance of artificial neural networks and deep learning, which have roots in cybernetics and historical mathematical foundations. This historical trajectory underscores the interdisciplinary nature of AI, influenced by philosophical, technological, and societal factors.
What is the evolution and current state of BI technologies?4 answersBusiness Intelligence (BI) technologies have evolved over time to encompass a wide range of applications and tools for gathering, analyzing, and visualizing data to support decision-making activities in organizations. BI has its roots in earlier systems such as MIS, DSS, and EIS, but has expanded to include technologies like data collection and storage, multidimensional data analysis, self-service tools, business analytics, modeling and simulation, text analytics, artificial intelligence, communication and collaboration platforms, and technology deployment issues. BI has transitioned from being focused on structured data to being able to operate on textual data as well, allowing for a more comprehensive analysis of the full spectrum of data within a corporation. Today, BI is considered a strategic initiative and is recognized as instrumental in driving business effectiveness and innovation. It is a process that involves both getting data into a data warehouse and accessing that data for enterprise reporting, OLAP, querying, and predictive analytics. The field of BI is constantly evolving, with new technologies like Big Data analytics and self-service tools gaining popularity.
What is IDW interpolation?4 answersIDW interpolation is a spatial statistics technique used to estimate values at locations where data is not observed. It is commonly used in various fields such as predicting power output of solar power systems, generating continuous surfaces like Digital Elevation Models (DEMs), and mapping 3D distributions of heterogeneous pollutants. IDW interpolation works by assigning weights to neighboring data points based on their distances from the interpolated point. The weights are then used to calculate the estimated value at the interpolated point. The accuracy of IDW interpolation can vary depending on factors such as the number of inputs and the distance between observation points. In some cases, IDW interpolation has been shown to outperform other methods like Artificial Neural Networks (ANNs).
What is interpolation ?5 answersInterpolation is the process of estimating unknown values between known data points. It is widely used in various fields such as data mining, environmental modeling, and scientific and engineering problems. Interpolation allows us to make intelligent estimations of data between known points and simplify complicated functions by fitting a smooth curve through a given set of points. The most commonly used method for interpolation is polynomial interpolation, which includes Lagrange interpolation and Newton interpolation. Other methods include stepwise linear interpolation, Hermite interpolation, cubic splines, and Chebyshev nodes. Interpolation can also be used for data fitting, with the linear squares method being a typical approach. Newton's method is a popular interpolation method that provides smaller error values compared to the Lagrange interpolation method.