![]() ![]() This option is only available on devices whose camera hardware supports this feature. Allows you to select the metering point from any point on the picture. If you want point metering, but not centered, you can use touch metering (if available). ![]() the focus rectangle is not centered) the metering point will still be centered. Use the area of the focus rectangle when it is centered on the viewfinder. Use the central part of the picture to meter light. Select which zones to use from the picture to meter light. Select the ISO value: automatic (AUTO) or in the range from ISO 50 to ISO 3200, depending on the device (some sensitivities may not be available, or may take no effect if Camera FV-5 is unable to detect the available ISO range of your device). Read more on this on chapter Automatic exposure bracketing (p. If exposure bracketing (BRK) is enabled, the exposure compensation will compensate the bracketing exposures, and the bracketing number of pictures and step will limit the EV range. A range of and a step of ½ stop is typical. The EV range and step vary across devices. A value of +1 effectively doubles the exposure time, whereas a value -1 halves the exposure time. Exposure compensation (EV) ¶Īdjust the compensation of the exposure time. White balance is reset to AWB, focus mode to AF, metering mode to matrix, ISO to Auto and exposure compensation to +/- 0. The device will produce a short vibration to confirm that the setting was reset to its default and the icons will also reflect the change. You can reset altered photographic parameters to their defaults by long-pressing on their corresponding buttons. ![]() What you can do with the photos taken with BRK The input argument illum specifies the illuminant as an RGB color and the input argument ax specifies the axes on which to plot the unit vector.Program modes, shooting utilities and flash settings The plotColorAngle function plots a unit vector of an illuminant in 3-D RGB color space. One algorithm might work better than the others for a particular image, but might perform poorly over the entire data set. Third, a full comparison of illuminant estimation algorithms should use a variety of images taken under different conditions. For example, for the image in this study, using the same pixels, the median color and the mean color of the neutral patches are 0.5 degrees apart, which in some cases can be more than the angular error of the illuminants estimated by different algorithms. It is common to use the median instead of the mean, which could shift the ground truth by a significant amount. Second, the ground truth illuminant is estimated as the mean color of the neutral patches. The ground truth illuminant of a scene can be better estimated using a spectrophotometer. However, this result should be taken with a grain of salt.įirst, the ground truth illuminant was measured using a ColorChecker chart and is sensitive to shot and sensor noise. This comparison of two classic illuminant estimation algorithms and a more recent one shows that Cheng's method, using the top and bottom 0.75% darkest and brightest pixels, wins for that particular image. Include Default Bottom and Top 3.5 Percent of Pixelsįirst, estimate the illuminant using the default percentage value of Cheng's PCA method, excluding those corresponding to the ColorChecker chart. Use the illumpca function to estimate illumination using Cheng's PCA algorithm. Finally, they perform a principal component analysis (PCA) on the retained pixels and return the first component as the estimated illuminant. These two groups correspond to strong gradients in the image. Their method consists in ordering pixels according to the norm of their projection along the direction of the mean image color, and retaining the bottom and top percentile. They show that Grey Edge can be improved by artificially introducing strong gradients by shuffling image blocks, and conclude that the strongest gradients follow the direction of the illuminant. Cheng's Principal Component Analysis (PCA) MethodĬheng's illuminant estimation method draws inspiration from spatial domain methods such as Grey Edge, which assumes that the gradients of an image are achromatic. ![]()
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