Hyperspectral imaging is an important technology in remote sensing, which is widely used in many fields, such as agriculture and forestry observation, environmental monitoring, deep space exploration, and so on. The miniaturization and low cost have become an important development direction for hyperspectral imagers. Simultaneously, obtaining images with high spatial resolution, high spectral resolution, and high signal-to-noise ratio (SNR) has become an urgent challenge in the development of miniaturized imaging spectrometers. Based on linear variable filter (LVF) spectroscopy technology and small pixel CMOS sensors, combining with time delay and integration (TDI) algorithm in digital domain, we proposed a digital integrated LVF spectral imaging method; then, a miniaturized hyperspectral imaging system, which weighs only 5 kg, was designed. To address the spectral aliasing problem of this new imaging method, we further proposed a calibration-based spectral restoration and enhancement algorithm. The experimental results showed that the miniaturized hyperspectral imager can achieve a ground sample distance (GSD) of 10 m at 500 km, an average spectral resolution of 5.6 nm, and SNR better than 30 dB.