Automatic energy-saving method for screen by using dynamic pixel dimming and nonlinear equation
A non-linear equation and pixel technology, applied in the direction of static indicators, instruments, etc., can solve the problems of reducing screen contrast, screen color cast, loss of screen image details, etc., to achieve the goal of reducing color loss, prolonging service life, and beautiful visual experience Effect
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Embodiment 1
[0052] refer to figure 1 , a method for automatic screen energy saving using dynamic pixel dimming and nonlinear equations, including the following steps:
[0053] Step S1: perform color and conversion on the input color image, and convert the picture in the RGB color gamut into the data in the YUV color gamut;
[0054] Step S2: perform histogram statistics on the luminance Y channel converted in step S1, and the histogram vector after statistics is Hist_Y 1 , Hist_Y 1 The vector normalized to the [0, 65535] interval is Hist_Y 2 ;
[0055] Step S3: To Hist_Y 2 Perform correction processing to correct Hist_Y 2 becomes the desired curve vector Hist adjust ;
[0056] Step S4: solve the Hist obtained in step S3 adjust Normalize to L gray level, the normalized matrix is Hist_L;
[0057] Step S5: Calculate Hist using formula (6) L The cumulative histogram of ;
[0058] Step S6: perform energy-saving processing on the OLED screen through the energy-saving formula (7);
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Embodiment 2
[0062] refer to Figure 1-4 , on the basis of the first embodiment, it is another preferred embodiment of the same invention, using dynamic pixel dimming and nonlinear equation screen automatic energy-saving method, including the following steps:
[0063] Step S1: Perform color and conversion on the input color image, and convert the image in the RGB color gamut into data in the YUV color gamut
[0064] The color conversion formula is as follows
[0065]
[0066] Step S2: perform histogram statistics on the luminance Y channel converted in step S1, and the histogram vector after statistics is Hist_Y 1 , Hist_Y 1 The vector normalized to the [0, 65535] interval is Hist_Y 2 ;
[0067] Specifically, histogram statistics are performed on the luminance Y channel converted in step S1, and the statistics vector is Hist_Y 1 , according to formula (2), put Hist_Y 1 The vector of is normalized in the interval [0, 65535].
[0068]
[0069] Hist mas =MAX(Hist_Y 2 ) (3)
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