The current document is directed to digital-image-normalization methods and systems that generate accurate intensity mappings between the intensities in two digital images. The intensity mapping generated from two digital images is used to normalize or adjust the intensities in one image in order to produce a pair of normalized digital images to which various types of change-detection methodologies can be applied in order to extract differential data. Accurate intensity mappings facilitate accurate and robust normalization of sets of multiple digital images which, in turn, facilitates many additional types of operations carried out on sets of multiple normalized digital images, including change detection, quantitative enhancement, synthetic enhancement, and additional types of digital-image processing, including processing to remove artifacts and noise from digital images.

An image detection obtains original image. The original image is corrected to obtain a corrected image. Median filtering is performed on the corrected image to obtain a filtered image. A contrast of the filtered image is adjusted to obtain an adjusted image. Bilateral filtering is performed on the adjusted image to obtain an enhanced image. Defects in the enhanced image is detected. The method can detect defects in images accurately and efficiently.

An image detection obtains original image. The original image is corrected to obtain a corrected image. Median filtering is performed on the corrected image to obtain a filtered image. A contrast of the filtered image is adjusted to obtain an adjusted image. Bilateral filtering is performed on the adjusted image to obtain an enhanced image. Defects in the enhanced image is detected. The method can detect defects in images accurately and efficiently.

A piecewise linear function for image tone conversion is easily corrected. An image processing apparatus first obtains a piecewise linear function for image tone conversion. Next, the image processing apparatus performs correction, in a case where the magnitude of the slope of the piecewise linear function in a processing target piece is larger than a predefined upper limit value, on the piecewise linear function so as to bring the magnitude of the slope of the piecewise linear function in the processing target piece to the upper limit value by changing the value of the end point of the processing target piece. The image processing apparatus performs the correction sequentially on a piece adjacent to the processing target piece.

A piecewise linear function for image tone conversion is easily corrected. An image processing apparatus first obtains a piecewise linear function for image tone conversion. Next, the image processing apparatus performs correction, in a case where the magnitude of the slope of the piecewise linear function in a processing target piece is larger than a predefined upper limit value, on the piecewise linear function so as to bring the magnitude of the slope of the piecewise linear function in the processing target piece to the upper limit value by changing the value of the end point of the processing target piece. The image processing apparatus performs the correction sequentially on a piece adjacent to the processing target piece.

Disclosed is a display apparatus. The display apparatus obtains first characteristic information, which is provided according to a plurality of sections of content and corresponds to an image characteristic of a section to be displayed among the plurality of seconds, from a signal received in the signal receiver, obtains first image-quality setting information for setting image quality of the section based on the obtained first characteristic information, obtains second characteristic information corresponding to an image characteristic of a frame included in the section from the frame, obtains second image-quality setting information for setting image quality of the frame based on the obtained first image-quality setting information and the obtained second characteristic information, and controls the display to display an image of the frame, the image quality of the frame being set based on the obtained second image-quality setting information.

Disclosed is a display apparatus. The display apparatus obtains first characteristic information, which is provided according to a plurality of sections of content and corresponds to an image characteristic of a section to be displayed among the plurality of seconds, from a signal received in the signal receiver, obtains first image-quality setting information for setting image quality of the section based on the obtained first characteristic information, obtains second characteristic information corresponding to an image characteristic of a frame included in the section from the frame, obtains second image-quality setting information for setting image quality of the frame based on the obtained first image-quality setting information and the obtained second characteristic information, and controls the display to display an image of the frame, the image quality of the frame being set based on the obtained second image-quality setting information.

A method for inverse tone mapping includes obtaining a histogram of a low dynamic range image, called LDR image and obtaining an ITMO function, allowing obtaining a pixel value of a High Dynamic Range image, called HDR image, from a pixel value of the LDR image and a gain function depending on said pixel value of the LDR image. A search process is applied using the obtained histogram to identify areas of the LDR image producing bright areas in the HDR image when the ITMO function is applied on said LDR image. Information representative of the bright areas is used to determine when modifying the gain function to ensure the HDR image respects at least one predefined light energy constraint.

Disclosed is a 3D reconstruction method for obtaining, from a 2D colour image of a human face with a visible toothed portion (1), a single reconstructed 3D surface of the toothed portion and of the facial portion (4) without toothed portion. The method comprises segmenting the 2D image into a first part (22) corresponding to the toothed portion (1) and a second part corresponding to the facial portion (4) without said toothed portion, enhancing the first part of the 2D image in order to modify the photometric characteristics, and generating a 3D surface of the face reconstructed from the enhanced first part of the 2D image and from the second part of the 2D image. The obtained 3D surface of the face is suitable for simulating a dental treatment, by substituting on the area of the 3D surface corresponding to the toothed portion (1), another 3D surface corresponding to the toothed portion after the projected treatment.

Disclosed is a 3D reconstruction method for obtaining, from a 2D colour image of a human face with a visible toothed portion (1), a single reconstructed 3D surface of the toothed portion and of the facial portion (4) without toothed portion. The method comprises segmenting the 2D image into a first part (22) corresponding to the toothed portion (1) and a second part corresponding to the facial portion (4) without said toothed portion, enhancing the first part of the 2D image in order to modify the photometric characteristics, and generating a 3D surface of the face reconstructed from the enhanced first part of the 2D image and from the second part of the 2D image. The obtained 3D surface of the face is suitable for simulating a dental treatment, by substituting on the area of the 3D surface corresponding to the toothed portion (1), another 3D surface corresponding to the toothed portion after the projected treatment.