Video Research Resources

• Video Processing Architecture
  Overview of video processing architecture.
• Backend Video Processing
  Discussion of video processing performed between the video decoder and video monitor.
• Local Direction Detector
  Discussion of method to estimate edge or texture element direction.
• Implementation of FIR using Downsampling
  Discussion of how filtering with downsampling is used in video processing.
• Narrow Passband Spectrum Filtering by Downsampling and Trivial Rotation
  Discussion of narrowband filtering with downsampling and rotation is used in video processing.
• Estimation of Complex Signal Magnitude and Angle
  Discussion of method in DSP to estimate complex signal magnitude and angle.

Video Broadcasting

• Analog TV Standards
  Comparison of major TV standards.
• Analog TV Modulation
  Discussion of video signal modulation for different standards.
• Analog TV Demodulation
  Discussion of video signal demodulation for different standards.
• FM Audio Demodulator
  Discussion of audio demodulation for terrestrial analog TV.
• ATSC Digital Terrestrial TV Transmitter
  Discussion of terrestrial digital TV broadcast standard.
• ATSC Digital Terrestrial TV Receiver
  Discussion of 8-VSB receiver processing.
• Equalizer for ATSC Digital Terrestrial TV Receiver
  Discussion of handling multipath propagation for terrestrial TV broadcast.
• Digital Video Broadcasting for Cable Systems DVB-C
  Discussion of cable DVB transmitter and receiver processing.
• Digital Video Broadcasting for Satellite Systems DVB-S
  Discussion of satellite DVB transmitter and receiver processing.
• Digital Video Broadcasting for Terrestrial Systems DVB-T
  Discussion of transmitter processing for terrestrial TV broadcast.
• DVB-T Receiver
  Discussion of receiver processing for terrestrial TV broadcast.
• OFDM Modulation
  Discussion of OFDM modulation processing used in terrestrial TV broadcast.

Distributed Video Coding

• Distributed Video Coding (DVC)
  Discussion of DVC used in applications with limited resources.
• Pixel-Domain Wyner-Ziv Coding
  Discussion of pixel domain method for DVC with very low computational encoder complexity.
• Transform-Domain Wyner-Ziv Coding
  Discussion of transform domain method for DVC with very low computational encoder complexity.
• Correlation Noise in Wyner-Ziv Video Coding
  Discussion of correlation noise used in DVC systems.

Interactive Video

• Interactive Video
  Discussion of techniques for enabling user interaction with video.

Video Compression

• Video Compression
  Discussion of video compression techniques and standards.
• H.264/AVC Syntax
  Discussion of H.264/AVC Syntax used in video compression.
• H.264/AVC Transform
  Discussion of H.264/AVC transform algorithm.
• Profiles and Levels in H.264/AVC
  Discussion of different profiles and levels used in encoding and decoding of video.

Video Conferencing

• Video Conferencing Technology
  Discussion of video conferencing applications and requirements.

Video Description

• Video Description Technology
  Discussion of descriptive technology used for visually impaired.

Video Streaming

• Video Streaming Technology
  Discussion of various methods for streaming video over networks.
• Video Streaming to Mobile Devices
  Challenges of streaming video to cell phones and other mobile devices.
• Mobile Live Streaming
  Discussion of methods for efficient video streaming to mobile platforms.
• Mobile Video-on-Demand
  Discussion of methods for delivery of VoD to mobile platforms.
• User Adaptive Video Streaming
  Discussion of leveraging user viewing information and potential content interaction for improved QoS.
• Adaptive Bitrate Streaming
  Discussion of method for managing streaming multimedia.
• Progressive Download
  Discussion of media streaming using progressive download.
• QoE for Streaming Video
  Discussion of how QoE is used to improve customer experience for video streaming.
• Video Streaming Protocols
  Discussion of RTP, RTCP and RTSP protocols used for video streaming.
• P2P Video Streaming
  Discussion of methods for P2P video streaming.
• P2P Network
  Discussion of different P2P networks used for streaming video.
• P2P Mesh-Based Live Video Streaming
  Discussion of meshed based P2P video streaming.
• P2P Multi-Tree Based Live Video Streaming
  Discussion of multi-tree based method for P2P video streaming.
• P2P Single Tree Based Video Streaming
  Discussion of tree based method for P2P video streaming.
• P2P Video on Demand
  Discussion of methods for streaming P2P video on demand.
• P2P on Demand Mesh-Based Live Video Streaming
  Discussion of methods for P2P video streaming.
• Security in P2P Video Streaming
  Discussion of security issues with P2P networks and video streaming.

Video Surveillance

• Video Surveillance Technology
  Discussion of different video surveillance systems in use.
• Histogram of Oriented Gradients (HOG) for Object Detection
  Discussion of method for object detection using shapes.
• Face Detection using Viola-Jones Algorithm
  Discussion of using V-J algorithm to detect facial features.
• AdaBoost Training Algorithm for Viola-Jones Object Detection
  Discussion of method to identify features and construct the object detection classifier.
• Digital Video Surveillance Security Cameras
  Discussion of different types of video cameras used in video surveillance systems.
• Video Surveillance for Biometrics
  Discussion of using biometrics to for efficient searching of large databases.
• Remote Video Surveillance
  Discussion of different types of systems used for remote video surveillance.
• Comparison of JPEG2000 and H.264 for Video Surveillance/li>
  Comparison of JPEG200 and H.264 used for video surveillance.
• Human Detection and Tracking in Video Surveillance System
  Discussion of methods to detect human presence, behavior and identity.
• Speed Capture in Video Surveillance
  Discussion of methods for determining vehicle speed in video surveillance.
• Surveillance Video Coding with Background Preprocessing
  Discussion of methods for preprocessing background scenes in video surveillance.

Video Deinterlacing

• Deinterlacing
  Overview of deinterlacing processing.
• Basic Motion Adaptive Deinterlacer
  Discussion of how basic adaptive deinterlacing is used in video processing.
• Advanced Motion Adaptive Deinterlacer
  Discussion of how advanced adaptive deinterlacing is used in video processing.
• Advanced Motion Adaptive Directional Deinterlacer
  Discussion of how advanced directional deinterlacing is used in video processing.
• Basic Motion Detector For Motion Adaptive Deinterlacer
  Discussion of how motion detection is used in deinterlacing video.

Video Sharpening

• Video Sharpening
  Discussion of video sharpening methods used to enhance video.
• Video Sharpening with Controlled Granularity
  Discussion of how video sharpening is controlled in video processing.
• Video Sharpening with Controlled Granularity and Noise Coring
  Discussion of method to reduce high frequency noise during video sharpening.
• Video Vertical and Horizontal Sharpening with Diagonal Sharpening Control
  Method for reducing extra sharpening that occurs with vertical and horizontal sharpening.
• Overshoot for Video Sharpening
  Discussion of methods used to control video sharpening of edges.

Video Scaling

• Video Scaling
  Methods for scaling video output resolutions.
• Basic Video Scaler
  Discussion of polyphase filtering used in video processing.
• Basic Directional Video Scaler
  Discussion of how Directional Video Scaling is used in video processing.
• Combined Video Scaler and Sharpener
  Discussion on combining video functions to reduce algorithm complexity and increase performance.
• Scalable Video Compression based on Wavelets
  Discussion of using wavelet transform for scalable video compression.
• Embedded Zerotree in Wavelet Image Compression
  Discussion of using embedded zerotrees with wavelet video compression.

Video Noise Reduction

• Noise Reduction using Spatial Level Control Filter
  Discussion of spatial filtering used in video processing for reducing noise.
• Noise Reduction using Combined Linear-Median Filter
  Discussion of combined spatial filtering used in video noise reduction.
• Impulse Noise in TV Channels
  Discussion of impulse noise effects in video signals.
• Mosquito Noise Reduction
  Discussion of video processing used to reduce mosquito noise artifacts.
• Flesh Tone Noise Reduction Correction
  Discussion of methods used to reduce artificial looking skin.
• Impulse Noise Immunity for AGC
  Discussion of method to reduce impulse noise for AGC of video signals.
• Interframe Noise Reduction for Video
  Discussion of interframe noise reduction in video processing.
• Blocking Artifact Reduction
  Discussion of method to reduce blocking artifacts in video.

Digital Watermarks

• Digital Watermarking
  Discussion of different watermarking methods.
• DCT Transform Digital Watermarking
  Discussion of of discrete cosine transform watermark method.
• Wavelet Transform Digital Watermarking
  Discussion of wavelet transform watermark method.
• Hadamard Transform Digital Watermarking
  Discussion of Hadamard transform watermark method.
• Digital Watermarking for H.264 Video Compression
  Discussion of watermark methods for H.264 video.

JPSEC and JPEG2000

• Wireless JPEG2000 Transmission and Unequal Error Protection using JPWL
  The JPWL standard is introduced. The header protection and unequal error protection capabilities of the standard are examined.
• Secure Faxing with JPSEC
  Faxing documents using Secure JPEG 2000, also referred to as JPSEC, is a method to secure image contents with stronger encryption and data integrity than what is provided by T.30.
• JPEG2000 Image Transmission using JPIP
  The scalable properties of JPEG2000 interactivity protocol (JPIP) are discussed. Some applications suchas medical applications or image access on restricted devices is explored.
• Secure JPEG2000 (JPSEC) Images
  Security in JPEG2000 is addressed by Part 8  of the ITU standard (T.807) known as JPSEC. We consider some of the possibilities of using the selective encoding of JPSEC with the
  scalability properties of JPEG2000.
• JPEG2000 Rate and Quality Scalability
  The scalable properties of JPEG2000 are explored including resolution scalability and quality scalability. It is explained how JPEG2000 uses EBCOT to accomplish this scalability.
• Document Signature by Multiple Parties
  This page describes a method to allow multiple users to simultaneously sign a document using fax and Internet technologies. Either digital or physical signatures may be used to sign the document.
• Wavelet Transform for Sparsity in JPEG2000
  The discrete wavelet transform (DWT) is used in the compression of images in the JPEG2000 protocol. Compared to the DCT used in the original JPEG compression, it allows for scalability and increased image quality in the compressed image.

Compressed Sensing

• Compressed Sensing of Images
  Compressed sensing can be used to simplify the sampling procedure for complex imaging systems. Such systems include MRI imaging and extremely high resolution optical imaging.
• Enhanced Security Based on Under-Determination in Compressed Sensing
  We present a feature of the technique of joint compression and encryption by compressed sensing. This feature makes messages encoded in this way more secure than messages secured by standard methods.
• Compressed Sensing for Error Protection in JPWL
  Compressed sensing techniques are examined as an alternative for Reed-Solomon error correction within the JPWL framework.
• Error Correction Using Compressed Sensing Techniques
  Compressed sensing is a technique where a sparse signal can be undersampled and reconstructed using convex minimization techniques. We show how compressed sensing techniques can be used as a forward error correction scheme.
• Gradient Projection Reconstruction of Compressed Sensing Signals
  A gradient projection algorithm is introduced with the intention of decreasing the computational complexity of the compressed sensing reconstruction problem.
• Compressed Sensing in JPSEC
  Compressed sensing (CS) can be used as the encryption mechanism within the JPSEC protocol. The inherent properties of CS allow for some desirable properties within an image encryption scheme.
• Secrecy of Cryptography With Compressed Sensing
  The secrecy of images encoded using compressed sensing is examined. The standard deviation of the guessed sampling matrix is calculated and the impact this has on the security of the image is explored.
• Overview of Encryption of Compressed Sensed Images
  Compressed sensing (CS) as an image encryption mechanism is explored.
• Single Pixel Camera
  A single pixel camera concept is presented. This camera allows a physical realization of a compressed sensing (CS) system, where the sampling matrix is created using a digital micromirror device (DMD).
• Background Subtraction using Compressed Sensing
  Compressed sensing is used to remove the background from an image. This allows for a low complexity background subtraction algorithm which can be implemented directly at the camera  for use in surveillance or motion detection.
• Multipath Channel Estimation with Compressed Sensing
  We propose a method for using compressed sensing (CS) to find the multipath channel coefficients in a sparse channel. The channel is sensed using a pseudo-random process and the coefficients are determined using l1 minimization  techniques.
• Interference Cancellation in Compressed Sensed Signals
  A method is presented by which, for two compressed sensed signals, a signal of interest can be separated from an interferer based on some assumptions about the signals.
• Adaptive Parity Error Detection for Compressive Imaging
  Traditional image compression is very sensitive to bit errors from a lossy channel. By using compressed sensing to compress an image, the error resiliency of an encoded image is greatly increased.
• Noise Resiliency with Compressed Sensing
  Noise Resiliency with Compressed Sensing.
• Terahertz Imaging for Security using Compressed Sensing
  Terahertz Imaging for Security using Compressed Sensing.

Particle Swarm Optimization

• Motion Tracking using Particle Swarm Optimization
  A Particle Swarm Optimization based algorithm for motion tracking.
• Image Compression using Compressed Sensing (CS) and Particle Swarm
  Optimization (PSO)
  A method is described for using PSO and Compressed Sensing for image compression.