Abstract: Systems, methods and computer program products are disclosed for resampling a digital image. According to an implementation, a source image can be presharpened and upsampled to a first upsampled image having a specified image size and a first level of presharpening. The source image is also presharpened and upsampled to a second upsampled image having the specified image size and second level of presharpening that is less than the first level of presharpening. The first and second upsampled images are deblurred. A binary edge mask image is generated from the deblurred, upsampled images. The binary edge mask image is dilated and blurred to generate a deep mask image. The first and second, deblurred upsampled images are blended together using the deep mask image.

Abstract: A system, method and computer-readable medium are disclosed that uses previously transmitted video frames and associated video frame content information to reduce the amount of information to be transmitted from a sending device to a receiving device during a video transmission.

Abstract: Psychovisual image compression techniques are disclosed that compress pixel data by a fixed compression ratio with little or no perceptual loss of detail. In some implementations, a psychovisual compression process is selected among several psychovisual compression processes based on characteristics of the pixel data. Compression is achieved during encoding by discarding psychovisually unnecessary bits from the pixel data. The psychovisual compression processes can be implemented in hardware and operate on scan lines of pixels captured by the image sensor. The psychovisual compression techniques can be used with image compression techniques to compress further the pixel data.

Abstract: A three-dimensional (“3D”) avatar can be automatically created that resembles the physical appearance of an individual captured in one or more input images or video frames. The avatar can be further customized by the individual in an editing environment and used in various applications, including but not limited to gaming, social networking and video conferencing.

Abstract: Embodiments provide methods and systems for the modeling and analysis of visual fields. Methods for global and regional measurement of visual sensitivity and quantification of field loss are provided in accordance with various embodiments. Further embodiments provide systems and methods for the diagnosis of diseases affecting the visual field. In addition, embodiments provide methods and systems for measuring and quantifying the volume of the Hill of Vision for an individual subject.

Abstract: Systems, methods and computer program products are disclosed for automatic image sharpening. Automatic image sharpening techniques are disclosed that automatically bring a blurred image into focus. Techniques for reducing edge ringing in sharpened images are also disclosed. According to implementations, a computer-implemented method includes determining a normalized entropy of a first image, calculating a correlation target based on the normalized entropy, automatically determining a blur radius of a de-convolution kernel that causes a cosine of a first radial power spectrum of the kernel and a second radial power spectrum of a reconstruction of the first image to approximate the correlation target and generating a second image based on the blur radius.

Abstract: A system, method and computer-readable medium are disclosed that uses previously transmitted video frames and associated video frame content information to reduce the amount of information to be transmitted from a sending device to a receiving device during a video transmission.

Abstract: Systems, methods and computer program products are disclosed for resampling a digital image. According to an implementation, a source image can be presharpened and upsampled to a first upsampled image having a specified image size and a first level of presharpening. The source image is also presharpened and upsampled to a second upsampled image having the specified image size and second level of presharpening that is less than the first level of presharpening. The first and second upsampled images are deblurred. A binary edge mask image is generated from the deblurred, upsampled images. The binary edge mask image is dilated and blurred to generate a deep mask image. The first and second, deblurred upsampled images are blended together using the deep mask image.

Abstract: Systems, methods and computer program products are disclosed for resampling a digital image. According to an implementation, a source image can be presharpened and upsampled to a first upsampled image having a specified image size and a first level of presharpening. The source image is also presharpened and upsampled to a second upsampled image having the specified image size and second level of presharpening that is less than the first level of presharpening. The first and second upsampled images are deblurred. A binary edge mask image is generated from the deblurred, upsampled images. The binary edge mask image is dilated and blurred to generate a deep mask image. The first and second, deblurred upsampled images are blended together using the deep mask image.

Abstract: Psychovisual image compression techniques are disclosed that compress pixel data by a fixed compression ratio with little or no perceptual loss of detail. In some implementations, a psychovisual compression process is selected among several psychovisual compression processes based on characteristics of the pixel data. Compression is achieved during encoding by discarding psychovisually unnecessary bits from the pixel data. The psychovisual compression processes can be implemented in hardware and operate on scan lines of pixels captured by the image sensor. The psychovisual compression techniques can be used with image compression techniques to compress further the pixel data.

Abstract: Systems, methods and computer program products are disclosed for automatic image sharpening. Automatic image sharpening techniques are disclosed that automatically bring a blurred image into focus. Techniques for reducing edge ringing in sharpened images are also disclosed. According to implementations, a computer-implemented method includes determining a normalized entropy of a first image, calculating a correlation target based on the normalized entropy, automatically determining a blur radius of a de-convolution kernel that causes a cosine of a first radial power spectrum of the kernel and a second radial power spectrum of a reconstruction of the first image to approximate the correlation target and generating a second image based on the blur radius.

Abstract: Systems, methods and computer program products are disclosed for resampling a digital image. According to an implementation, a source image can be presharpened and upsampled to a first upsampled image having a specified image size and a first level of presharpening. The source image is also presharpened and upsampled to a second upsampled image having the specified image size and second level of presharpening that is less than the first level of presharpening. The first and second upsampled images are deblurred. A binary edge mask image is generated from the deblurred, upsampled images. The binary edge mask image is dilated and blurred to generate a deep mask image. The first and second, deblurred upsampled images are blended together using the deep mask image.

Abstract: A three-dimensional (“3D”) avatar can be automatically created that resembles the physical appearance of an individual captured in one or more input images or video frames. The avatar can be further customized by the individual in an editing environment and used in various applications, including but not limited to gaming, social networking and video conferencing.

Abstract: Embodiments provide methods and systems for the modeling and analysis of visual fields. Methods for global and regional measurement of visual sensitivity and quantification of field loss are provided in accordance with various embodiments. Further embodiments provide systems and methods for the diagnosis of diseases affecting the visual field. In addition, embodiments provide methods and systems for measuring and quantifying the volume of the Hill of Vision for an individual subject.

Abstract: Image data to be compressed is first converted from the RGB domain into a gamma-powered YUV domain. A wavelet transform then separates image data into high- and low-detail sectors, incorporating a dynamic scaling method, allowing for optimal resolution. The output data from the wavelet transform is then quantized according to an entropy-prediction algorithm that tightly controls the final size of the processed image. An adaptive Golomb engine compresses the data using an adaptive form of Golomb encoding in which mean values are variable across the data. Using variable mean values reduces the deleterious effects found in conventional Golomb encoding in which localized regions of similar data are inefficiently coded if their bit values are uncommon in the data as a whole. Inverse functions are applied to uncompress the image, and a fractal dithering engine can additionally be applied to display an image on a display of lower color depth.

Abstract: The invention is a cryptographic system using chaotic dynamics. A chaotic system is used to generate a public key and an adjustable back door from a private key. The public key is distributed and can be used in a public key encryption system. The invention can also be used for authentication purposes. The adjustable back door of the invention can be used in conjunction with the public key to derive the private key. The degree of difficulty involved in deriving the private key is dependent on the adjustable back door. That is the value of the back door can be adjusted to vary the difficulty involved in deriving the private key.

Abstract: A method of generating a digital signature includes generating a first random number from a finite field of numbers, and generating field elements defining a first point on an elliptic curve defined over the finite field of numbers by performing elliptic curve arithmetic on the first random number and an initial public point on the elliptic curve. The method continues by generating a product from a field element, a private key, and a second random number received from a challenger seeking verification of a digital signature, and generating a signature component by summing the product and the first random number. The signature component is reduced using one or more modular reduction operations, using a modulus equal to an order of the elliptic curve, and then the reduced signature component and the field elements are sent to the challenger as a digital signature for verification by the challenger.

Abstract: Lossless compression and the corresponding decompression of image and audio data are enabled using a combination of dynamic prediction and Golomb coding. First, data is converted from the RGB domain into the YUV domain. Next, a dynamic prediction algorithm is run to express pixel values as differential values rather than original bit values. Prediction coefficients are re-evaluated on the fly enabling additional compression because of more accurate predictors. An Adaptive Golomb Engine next performs an additional compression step, using an adaptive form of Golomb encoding in which mean values are variable across the data. The use of variable mean values reduces the deleterious effects found in conventional Golomb encoding in which localized regions of similar data are inefficiently coded if their bit values are uncommon in the data as a whole.

Abstract: A method of generating a digital signature includes generating a first random number from a finite field of numbers, and generating field elements defining a first point on an elliptic curve defined over the finite field of numbers by performing elliptic curve arithmetic on the first random number and an initial public point on the elliptic curve. The method continues by generating a product from a field element, a private key, and a second random number received from a challenger seeking verification of a digital signature, and generating a signature component by summing the product and the first random number. The signature component is reduced using one or more modular reduction operations, using a modulus equal to an order of the elliptic curve, and then the reduced signature component and the field elements are sent to the challenger as a digital signature for verification by the challenger.

Abstract: A three-dimensional (“3D”) avatar can be automatically created that resembles the physical appearance of an individual captured in one or more input images or video frames. The avatar can be further customized by the individual in an editing environment and used in various applications, including but not limited to gaming, social networking and video conferencing.