Michael T. Orchard

What is he best known for?

The fields of study he is best known for:

• Algorithm
• Artificial intelligence
• Computer vision

His primary scientific interests are in Artificial intelligence, Computer vision, Transform coding, Algorithm and Wavelet transform. His Artificial intelligence study frequently draws connections between adjacent fields such as Bilinear interpolation. The Computer vision study which covers Interpolation that intersects with Pixel.

Michael T. Orchard works mostly in the field of Transform coding, limiting it down to topics relating to Rate–distortion theory and, in certain cases, Multiple description coding, Pairwise comparison, Real image, Entropy encoding and Mixture model, as a part of the same area of interest. His Algorithm study combines topics from a wide range of disciplines, such as Image processing, Speech recognition and Theoretical computer science. He is researching Wavelet transform as part of the investigation of Wavelet and Pattern recognition.

His most cited work include:

• New edge-directed interpolation (1766 citations)
• Color quantization of images (436 citations)
• Overlapped block motion compensation: an estimation-theoretic approach (392 citations)

What are the main themes of his work throughout his whole career to date?

Michael T. Orchard focuses on Artificial intelligence, Computer vision, Algorithm, Wavelet and Wavelet transform. His research links Pattern recognition with Artificial intelligence. His study on Motion estimation, Motion compensation and Deblocking filter is often connected to Inter frame as part of broader study in Computer vision.

His Algorithm study incorporates themes from Speech recognition, Theoretical computer science and Mathematical optimization. In his study, Vector quantization and Coding gain is inextricably linked to Quantization, which falls within the broad field of Wavelet. Michael T. Orchard has included themes like Transform coding, Filter bank and Edge detection in his Wavelet transform study.

He most often published in these fields:

• Artificial intelligence (64.41%)
• Computer vision (45.76%)
• Algorithm (34.75%)

What were the highlights of his more recent work (between 2000-2012)?

• Algorithm (34.75%)
• Artificial intelligence (64.41%)
• Transform coding (26.27%)

In recent papers he was focusing on the following fields of study:

His primary areas of study are Algorithm, Artificial intelligence, Transform coding, Computer vision and Data compression. The concepts of his Algorithm study are interwoven with issues in Image processing and Speech recognition. His research investigates the connection with Artificial intelligence and areas like Pattern recognition which intersect with concerns in Object detection.

Motion compensation, Bilinear interpolation, Stairstep interpolation, Bicubic interpolation and Nearest-neighbor interpolation are the subjects of his Computer vision studies. The Data compression study combines topics in areas such as Computational complexity theory and Error detection and correction. His study in the fields of Wavelet packet decomposition under the domain of Wavelet overlaps with other disciplines such as Construct and Face detection.

Between 2000 and 2012, his most popular works were:

• New edge-directed interpolation (1766 citations)
• Multiple description coding using pairwise correlating transforms (347 citations)
• A fast direct Fourier-based algorithm for subpixel registration of images (299 citations)

In his most recent research, the most cited papers focused on:

• Algorithm
• Artificial intelligence
• Computer vision

Michael T. Orchard spends much of his time researching Algorithm, Transform coding, Computer vision, Interpolation and Artificial intelligence. His study in the field of Data compression, Adaptive filter and Motion compensation also crosses realms of Redundancy. His Data compression research is multidisciplinary, incorporating elements of Image compression, Error detection and correction, Feature and Statistical model.

He combines subjects such as Speech recognition and Theoretical computer science with his study of Transform coding. His research in Pixel, Bicubic interpolation, Bilinear interpolation, Multivariate interpolation and Trilinear interpolation are components of Computer vision. His studies in Stairstep interpolation, Linear interpolation and Nearest-neighbor interpolation are all subfields of Interpolation research.