A system and method for image processing are provided. A pre-processed image may be obtained. The pre-processed image may be decomposed into a low-frequency image and a high-frequency image. At least one grayscale transformation range may be determined based on the low-frequency image. At least one grayscale transformation parameter may be determined based on the at least one grayscale transformation range. The low-frequency image may be transformed based on the at least one grayscale transformation parameter to obtain a transformed low-frequency image. A transformed image may be generated by reconstructing the transformed low-frequency image and the high-frequency image.

A system and method for image processing are provided. A pre-processed image may be obtained. The pre-processed image may be decomposed into a low-frequency image and a high-frequency image. At least one grayscale transformation range may be determined based on the low-frequency image. At least one grayscale transformation parameter may be determined based on the at least one grayscale transformation range. The low-frequency image may be transformed based on the at least one grayscale transformation parameter to obtain a transformed low-frequency image. A transformed image may be generated by reconstructing the transformed low-frequency image and the high-frequency image.

A method and apparatus for processing hologram image data capable of optimizing image quality of a hologram image are provided. The image processing method includes receiving input image data, reading a header included at a predetermined location in the input image data, and generating hologram data configured to display a hologram image by performing a Fourier calculation and pixel encoding on the input image data based on at least one parameter recorded in the header, wherein the at least one parameter recorded in the header includes at least one of depth information, scale information, and gamma information.

A method and apparatus for processing hologram image data capable of optimizing image quality of a hologram image are provided. The image processing method includes receiving input image data, reading a header included at a predetermined location in the input image data, and generating hologram data configured to display a hologram image by performing a Fourier calculation and pixel encoding on the input image data based on at least one parameter recorded in the header, wherein the at least one parameter recorded in the header includes at least one of depth information, scale information, and gamma information.

Systems and methods are disclosed for an ultrasound system. In various embodiments, a system is configured to receive echo data corresponding to a detection of an echo of a pulse signal, generate a set of transformations based on the echo data, and generate a set of point estimates for a frequency dependent filtering coefficient of a spectral response. The system is further configured to extract a set of attenuation coefficients based on the set of point estimates for the frequency dependent filtering coefficient and generate image data for the material of interest based on the set of attenuation coefficients.

Systems and methods are disclosed for an ultrasound system. In various embodiments, a system is configured to receive echo data corresponding to a detection of an echo of a pulse signal, generate a set of transformations based on the echo data, and generate a set of point estimates for a frequency dependent filtering coefficient of a spectral response. The system is further configured to extract a set of attenuation coefficients based on the set of point estimates for the frequency dependent filtering coefficient and generate image data for the material of interest based on the set of attenuation coefficients.

A system includes an image sensor, an imaging pipeline, and a display device. The image sensor is configured to capture a first frame of pixel data. The imaging pipeline is coupled to the image sensor to receive the first frame of pixel data. The imaging pipeline includes an adaptive noise filter. The adaptive noise filter is configured to filter a pixel based on noise in the pixel. The imaging pipeline is configured to output a second frame of pixel data. The second frame of pixel data includes pixels filtered by the adaptive noise filter. The display device is coupled to the imaging pipeline to receive the second frame of pixel data. The display device is configured to display the second frame of pixel data.

A system includes an image sensor, an imaging pipeline, and a display device. The image sensor is configured to capture a first frame of pixel data. The imaging pipeline is coupled to the image sensor to receive the first frame of pixel data. The imaging pipeline includes an adaptive noise filter. The adaptive noise filter is configured to filter a pixel based on noise in the pixel. The imaging pipeline is configured to output a second frame of pixel data. The second frame of pixel data includes pixels filtered by the adaptive noise filter. The display device is coupled to the imaging pipeline to receive the second frame of pixel data. The display device is configured to display the second frame of pixel data.

A method to compute a variable number of image planes, which are selected to better represent the scene while reducing the artifacts on produced novel views. This method analyses the structure of the scene by means of a depth map and selects the position in the Z-axis to split the original image into individual layers. The method also determines the number of layers in an adaptive way.

A method of de-smearing an image includes capturing image data from an imaging sensor and collecting motion data indicative of motion of the sensor while capturing the image data. The motion data is collected at a higher frequency than an exposure frequency at which the image data is captured. The method includes modeling motion of the sensor based on the motion data, wherein motion is modeled at the higher frequency than the exposure frequency. The method also includes modeling optical blur for the image data, modeling noise for the image data, and forming a de-smeared image as a function of the modeled motion, the modeled blur, and the modeled noise, and the image data captured from the imaging sensor.