To provide effective technical means for the study of the crop growth in water stress response mechanism, drought monitoring, and precision irrigation, moisture content detection in different regions of maize live crop leaves and near the canopy is achieved.The large volume, large weight, low luminous flux hyperspectrometer is difficult to achieve live detection in the field. The small volume, small weight, high luminous flux NIR camera with filters to make it wavelength-resolved is expected to achieve live leaf moisture content imaging detection in the field. Based on the near-infrared hyperspectral data of live maize leaves, this study is to investigate the key parameters, including the characteristic wavelength position and number, bandwidth and offset limit. Among them, the simulation data of different bandwidths are based on the filter light transmission distribution function; the simulation data of the center wavelength shift under fixed bandwidths are based on the interpolation method. The research results showed that the feature wavelengths are 1 150 and 1 400 nm respectively, and the bandwidth is less than 100 nm, which can meet the requirements and find the filter products that meet the parameter conditions. When the bandwidth was 25 nm, the model set’s determination coefficient (R²) and root mean square error (RMSE) were 0.968 and 1.245%, respectively, and the prediction set was 0.960 and 1.298%, respectively. To infer that the model built with the filters is affected by the ambient temperature, the model within a fixed center wavelength is used to predict the simulation data of different offsets. When the drift was 0.05 nm, the model prediction errorunder non-drift conditions was about 3%, which could be neglected. The relationship between the center wavelength drift of the filter and the temperature is equivalent to that the ambient temperature in the range of 50 ℃ has little effect on the detection results. Thisresearch provides important technical parameter support and working range for the NIR camera with filters to form a multispectral imaging system detection device. The device’s construction has been started, and the realization of the device can provide new and effective means for modern agricultural crop physiology and production research.