Python 如何读取10位原始图像？其中包含RGB-IR数据

我想知道如何从我的10位原始数据（它有rgb ir imagedata）中提取rgb图像

如何用Python或MATLAB阅读

拍摄时的相机分辨率为1280x720： 室内照片 户外照片

摄像机型号：e-CAM40_CUMI4682_MOD

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非常感谢

我使用了以下图像处理阶段：

• 拜耳马赛克彩色通道分离
• 线性拉伸每个颜色通道
• 简单白平衡
• 将红外颜色通道替换为绿色（将图像转换为标准拜耳格式）
• 恢复拜耳马赛克
• 简单的伽马校正
• 德莫萨奇

我没有处理红外颜色通道，而是将其替换为绿色通道

根据您添加的RGB图像，我找到了订单。
CFA（滤色器阵列）顺序为：

B | G
-- --
IR| R

以下Matlab代码将图像处理为RGB：

srcN=1280；
srcM=720；
f=fopen（'image_raw.raw'，'r'）；
%读取为转置矩阵维度，并转置矩阵。
%原因是Matlab内存oreder是列主程序，并且
%原始图像存储在主行中（如C数组）。
I=fread（f，[srcN，srcM]，'uint16'）；
fclose（f）；
I＝I′；
%从范围[0,1023]转换为范围[0,1]（以双图像格式工作）。
I=I/（2^10-1）；
%拜耳镶嵌色通道分离
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%假设输入格式为GBRG拜耳马赛克格式。
%分离颜色组件。
B=I（1:2:end，1:2:end）；
G=I（1:2:end，2:2:end）；
IR=I（2:2:结束，1:2:结束）；
R=I（2:2:end，2:2:end）；
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%线性拉伸每个颜色通道。
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%线性streatch蓝色通道。
B=imadjust（B，stretchlim（B[0.020.98]），[]）；
%线性streatch绿色通道。
G=imadjust（G，stretchlim（G[0.020.98]），[]）；
%线性streatch红色通道。
R=imadjust（R，stretchlim（R[0.02 0.98]），[]）；
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%简单白平衡
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%中位数或R、G和B。
rgb_med=[中位数（R（：）、中位数（G（：）、中位数（B（：））]；
rgb_比例=最大值（rgb_-med）。/rgb_-med；
%缩放每个颜色通道，使其具有相同的中间值。
R=R*rgb_标度（1）；
G=G*rgb_标度（2）；
B=B*rgb_标度（3）；
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%恢复拜耳马赛克。
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%将拉伸的颜色通道插入I。
I（1:2:end，1:2:end）=B；
I（1:2:end，2:2:end）=G；
%I（2:2:end，1:2:end）=G；%将IR替换为绿色。
I（2:2:end，2:2:end）=R；
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%将IR替换为绿色-首先将绿色大小调整为图像的完整大小。
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
T=imresize（G[srcM，srcN]）；%T-临时绿色，尺寸1280x720
I（2:2:end，1:2:end）=T（2:2:end，1:2:end）；%将IR替换为绿色。
I=最大值（最小值（I，1），0）；%将I限制在范围[0,1]内。
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%简单伽马校正
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
γ=0.45；
I=I.^gamma；
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%德莫萨奇
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%转换为uint8（范围[0255]）。
I=uint8（圆形（I*255））；
RGB=demosaic（I，“bggr”）；
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
imshow（RGB）；

结果:

现在颜色正常了

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室外图像处理：

对室外图像进行“室内”处理，得到如下结果：

白树是近红外光谱穿透R、G和B像素（不仅仅是红外像素）的标志。
植被的叶绿素在近红外光谱中具有高反射。请参阅：，然后在谷歌上搜索。
需要从红色、绿色和蓝色通道中减去IR

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我使用了以下图像处理阶段：

• 拜耳马赛克彩色通道分离
• 从红色、绿色和蓝色通道中减去红外“剩余”。
• 线性拉伸每个颜色通道
• 简单白平衡
• 恢复拜耳马赛克
• 简单的伽马校正
• Demosaic
• 调整RGB图像的大小以降低分辨率

以下Matlab代码将室外图像处理为RGB：

srcN=1280；
srcM=720；
f=fopen（'ir_6.raw'，'r'）；
%读取为转置矩阵维度，并转置矩阵。
%原因是Matlab内存oreder是列主程序，并且
%原始图像存储在主行中（如C数组）。
I=fread（f，[srcN，srcM]，'uint16'）；
fclose（f）；
I＝I′；
%从范围[0,1023]转换为范围[0,1]（以双图像格式工作）。
I=I/（2^10-1）；
%拜耳镶嵌色通道分离
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%假设输入格式为GBRG拜耳马赛克格式。
%分离颜色组件。
B=I（1:2:end，1:2:end）；
G=I（1:2:end，2:2:end）；
IR=I（2:2:结束，1:2:结束）；
R=I（2:2:end，2:2:end）；
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%从R、G和B中减去IR“盈余”。
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%通过试错法对系数进行了调整。。。
ir_r=1.3；%130%的红外辐射被红色像素吸收？？？
ir_g=0.35；%35%的红外辐射被绿色像素吸收。
ir_b=0.3；%30%的红外辐射被蓝色像素吸收。
IR=imresize（IR，大小（I））；%将IR的大小调整为