Marvell International Limited

Marvellworld Trade Ltd.

Qualcomm Incorporated

Synaptics Corporation

Shilpi Sahu

Nikhil Balram

Sanjay Saran Garg

Richard David Taylor

Vipin Namboodiri

Bipasha Ghosh

Gwyn Edwards

Loren Tomasi

Kaip Sridhar

Mainak Biswas

Sujith Srinivasan

Ankit Ghiya

Vasudev Bhaskaran

Pawan Kumar Baheti

Ajit Deepak Gupte

Xiaoyun Jiang

Chiranjib Choudhuri

Min Li

Feng Li

Yunqiang Chen

Shu Fei Fan

Panikumar Gururaj Kallamballe

Edwards Gwyn

Techniques are described in which a device is configured to determine an overlap region between a first image and a second image, determine a first histogram based on color data included in the first image that corresponds to the overlap region, and determine a second histogram based on color data included in the second image that corresponds to the overlap region. The processor is further configured to determine, based on the first and second histograms, a mapping function that substantially maps the second histogram to the first histogram and apply the mapping function to the second image to generate a normalized second image with respect to the first image.

Color normalization for a multi-camera system

Systems, methods, and devices for enhancing an image are described herein. In some aspects, a device comprises a memory unit configured to store a left image and a right image. The left image and right image each depict a same scene from a different viewpoint. The device further comprises a coder configured to retrieve the left image and the right image from the memory unit. The coder is configured to determine a depth map based on a difference in spatial orientation between the left and right image. The device further comprises a processor coupled to the coder. The processor is configured to identify a portion of the left or right image selected by a user. The processor is further configured to determine an enhancement region surrounding the portion selected by the user based on the depth map. The processor is further configured to enhance the enhancement region.

Depth aware enhancement for stereo video

In some cases, conventional digital zoom techniques can lead to poor quality images. Disclosed are systems and methods for improving the quality of images generated by digital zoom. For example, in some embodiments, a parallel structure is utilized where an image is passed through a sharpener and a 2D directional upscaler at the same time. Upscaling operations are then performed on the sharpened image. The upscaled sharpened image is added to the output of the 2D directional upscaler to produce an enhanced image.

Digital zoom methods and systems

Method and apparatus for reducing random noise in digital video streams are described. In one innovative aspect, the device includes a noise estimator. The device also includes a motion detector configured to determine a motion value indicative of motion between two frames of the video stream, the motion value based at least in part on the noise value. The device further includes a spatial noise reducer configured to filter the image data based at least in part on a blending factor and the noise value. The device also includes a temporal noise reducer configured to filter the video data based on the motion value and the noise value. The device also includes a blender configured to blend the spatial and temporal filtered values to provide a weighted composite filtered output image.

Method and apparatus of reducing random noise in digital video streams

High-frequency noise is generated that approximates the appearance of traditional 'film grain' for a digital video signal. By adding a relatively small amount of film grain noise, the video can be made to look more natural and more pleasing to the human viewer. The digital film grain generator can generate film grain in real-time. The generated film grain is preferably free from spatial or temporal patterns. Level adaptivity adjusts the amount of variation permitted for each pixel within a programmable range.

Film grain generator

Systems and methods are provided for detecting sharpness among video fields. In certain implementations of the systems and methods, a plurality of video fields is received and a sharpness metric for each of the plurality of video fields is determined. The sharpness metric of a first video field is compared to the sharpness metric of a second video field among the plurality of video fields and a video field source of the first video field and the second video field is determined based on the comparison.

Systems and methods for determining video field sharpness

A system and method for enhancing the detail edges and transitions in an input video signal. This enhancement may be accomplished by enhancing small detail edges before up-scaling and enhancing large amplitude transitions after up-scaling. For example, detail edge enhancement (detail EE) may be used to enhance the fine details of an input video signal. An edge map may be used to prevent enhancing the large edges and accompanying mosquito noise with the detail enhancement. Noise may additionally be removed from the signal. After the fine details are enhanced, the signal may be up-scaled. Luminance transition improvement (LTI) or chrominance transition improvement (CTI) may be used to enhance the large transitions of the input video signal post scaler.

Split edge enhancement architecture

The invention includes a system and the associated method for decoding multiple video signals. The video signals may be component video, composite video or s-video signals each having multiple portions using a multimode video decoder. A selection stage may combine the multiple video signals and select some of their video signal portions for processing. The selection stage may time-multiplex some of the video signal portions. An analog to digital conversion stage may be shared by the time-multiplexing of the video signals. A decoder stage may decode the various signal portions and provide decoded output video signals. These feature may reduce the overall cost of the system. Various clock signals may be used to operate various stages of a multimode video decoder. Some of the clock signals may run at different frequencies and others may operate at a different phase.

Shared memory multi video channel display apparatus and methods

A shared memory video processor including signal processing circuitry. The signal processing circuitry may enable a noise reducer and a de-interlacer to share access to field buffers in a memory device to store various field lines. Some of the stored field lines may also be shared within the signal processing circuitry. The sharing of some stored field lines reduces overall memory bandwidth and capacity requirements. The signal processing circuitry may be capable of performing multiple field line processing. A set of field line buffers may be provided to store field lines for multiple field segments and may provide the data to the corresponding inputs of the signal processing circuitry. To further reduce storage, some of the field line buffers may also be shared among the signal processing circuitry.

A scaler positioning module may receive a video signal selected from among a plurality of video signals. The scaler positioning module may include scaler slots for arranging the signal path of the selected video signal through at least one scaler in the scaler positioning module. The scaler slots may enable the scaler positioning module to operate in three modes. The three modes may enable the scaler positioning module to output scaled data without memory operations, scale prior to a memory write, and scale after a memory read. A blank time optimizer (BTO) may receive data from the scaler positioning module at a first clock rate and distributed memory accesses based on a bandwidth requirement determination. The BTO may access memory at a second clock rate. The second clock rate may be slower than the first which may reduce memory bandwidth and enable another video signal to access memory faster.

A multi-purpose scaler utilizes a vertical scaler module and a moveable horizontal scaler module to resample a video signal either vertically or horizontally according to a selected scaling ratio. The moveable horizontal scaler module resides in one of two slots within the multi-purpose scaler architecture to provide either horizontal reduction or horizontal expansion as desired. The multi-purpose scaler is arranged to scale the video using non-linear 3 zone scaling in both the vertical and horizontal direction when selected. The multi-purpose scaler is arranged to provide vertical keystone correction and vertical height distortion correction when the video is presented through a projector at a non-zero tilt angle. The multi-purpose scaler is also arranged to provide interlacing and de-interlacing of the video frames as necessary.

Multi-purpose scaler

A method and system for detecting and estimating noise in a video signal. For example, detail edges may be identified in a plurality of pixels, wherein each detail edge has an edge magnitude value. The detail edges in the plurality of pixels may be identified by: determining one or more directionality values for the plurality of pixels by passing the input video signal through at least one directional filter, and identifying the detail edges by assigning edge magnitude values based on whether the one or more directionality values exceed predetermined threshold levels. An edge map of the detail edges may be created, where the edge map is configured to indicate areas of the plurality of pixels to be considered or ignored in estimating the noise in the input video signal. The noise in the input video signal may then be estimated based on the indicated areas of the edge map.

Method and apparatus for estimating noise in a video signal

A system and method for motion adaptively filtering a de-interlaced video signal. This motion adaptive filtering may be accomplished by using a motion value determined during motion adaptive de-interlacing. The motion value may be used to adjust the amount of filtering to be applied to the de-interlaced signal. Edges in the signal representing motion my be filtered more than static regions. A pixel by pixel difference between multiple signal frames, calculated during motion adaptive de-interlacing, may be used to determine the motion value. A motion adaptive filter may be implemented either separately from the motion adaptive de-interlacer or incorporated as part of the motion adaptive de-interlacer.

Post de-interlacer motion adaptive filter for smoother moving edges

A vector interpolator optimizes the conversion of an interlaced signal to a non-interlaced signal. The vector interpolator improves the visual clarity of slanted features in a displayed image by adjusting the luminance value of each pixel such that the appearance of 'steps' or 'jaggies' in the features is reduced. For each pixel, the vector interpolator determines a similarity measure for the pixels within a predetermined area around the pixel. From the similarity measure, an angle for interpolation is selected. The luminance value is then interpolated along the selected vector corresponding to the angle and applied to the pixel. One or more ambiguity measures such as a local edge count ambiguity measure may also be computed to indicate the reliability of the computed luminance value.

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Bengaluru, India

Shilpi Sahu