Abstract: Methods to generate, and devices to use, an adaptive tone curve generation operation are disclosed. Tone curves so generated have been found to produce stable tone mapping in a wide range of operational environments, including during multi-exposure fused images (e.g., during high dynamic range image fusion). In general, techniques are disclosed that use a content-load histogram in combination with image capture device noise information to adaptively bound a tone curve's slope and, therefore, the resulting tone curve. As used here, a content-load histogram is a histogram that captures spatial, color or other information carried by an image's pixels at various gray levels.

Abstract: Some embodiments provide a method that provides a graphical user interface (GUI) for color balancing an image. The method provides a display area for displaying the image. The method provides several color balance modes. The method provides a user interface (UI) control associated with a color balance mode in the several color balance modes. The UI control performs a color balance operation on the image by (1) identifying a color cast in the image and (2) modifying pixels in the image based on the pixels' luminance values in order to reduce the color cast in the image.

Abstract: Some embodiments provide a method of automatically color balancing an image. The method receives a selection of a user interface (UI) item to automatically color balance the image using a color balance tool that includes several color balance modes. In response to the selection, the method analyzes the image based on a set of criteria. Based on the analysis, the method automatically selects a color balance mode from the several color balance modes of the color balance tool. Upon selecting the color balance mode, the method uses the color balance mode to automatically apply a set of color balance operations to the image.

Abstract: Techniques to improve image fusing operations using intensity mapping functions (IMFs) are described. In one approach, when a reference image's pixel values are within its' IMF's useful range, they may be used to generate predicted secondary image pixel values. When the reference image's pixel values are not within the IMF's useful range, actual values from a captured secondary image may be used directly or processed further to generate predicted secondary image pixel values. The predicted and actual pixel values may be used to construct predicted secondary images that may be fused. In another approach, the consistency between pixel pairs may be used to generate consistency-based weighting factors that may be used during image fusion operations.

Abstract: Methods to generate, and devices to use, an adaptive tone curve generation operation are disclosed. Tone curves so generated have been found to produce stable tone mapping in a wide range of operational environments, including during multi-exposure fused images (e.g., during high dynamic range image fusion). In general, techniques are disclosed that use a content-load histogram in combination with image capture device noise information to adaptively bound a tone curve's slope and, therefore, the resulting tone curve. As used here, a content-load histogram is a histogram that captures spatial, color or other information carried by an image's pixels at various gray levels.

Abstract: Techniques to improve image fusing operations using intensity mapping functions (IMFs) are described. In one approach, when a reference image's pixel values are within its' IMF's useful range, they may be used to generate predicted secondary image pixel values. When the reference image's pixel values are not within the IMF's useful range, actual values from a captured secondary image may be used directly or processed further to generate predicted secondary image pixel values. The predicted and actual pixel values may be used to construct predicted secondary images that may be fused. In another approach, the consistency between pixel pairs may be used to generate consistency-based weighting factors that may be used during image fusion operations.

Abstract: Some embodiments provide a method that provides a graphical user interface (GUI) for color balancing an image. The method provides a display area for displaying the image. The method provides several color balance modes. The method provides a user interface (UI) control associated with a color balance mode in the several color balance modes. The UI control performs a color balance operation on the image by (1) identifying a color cast in the image and (2) modifying pixels in the image based on the pixels' luminance values in order to reduce the color cast in the image.

Abstract: Some embodiments provide a method of automatically color balancing an image. The method receives a selection of a user interface (UI) item to automatically color balance the image using a color balance tool that includes several color balance modes. In response to the selection, the method analyzes the image based on a set of criteria. Based on the analysis, the method automatically selects a color balance mode from the several color balance modes of the color balance tool. Upon selecting the color balance mode, the method uses the color balance mode to automatically apply a set of color balance operations to the image.

Abstract: The probability of a chromaticity being a white point of image scene illumination is estimated by convolving a chromaticity histogram with a function of log probability distribution of chromaticities under an illuminant.

Abstract: A white point of scene illumination is determined by using a chromaticity histogram that is weighted for brightness.

Abstract: The probability of a chromaticity being a white point of image scene illumination is estimated by convolving a chromaticity histogram with a function of log probability distribution of chromaticities under an illuminant.