The dynamic range of the intensity of long-wave infrared (LWIR) cameras are often more than 8bit and its images have to be visualized using histogram equalization and so on. Many visualization methods do not consider effects of noise, which must be taken care of in real situations. We propose a novel LWIR images visualization method based on gradient-domain processing or gradient mapping. Processing based on intensity and gradient power in the gradient domain enables visualizing LWIR images with noise reduction. We evaluate the proposed method quantitatively and qualitatively and show its effectiveness.
A sequential transfer-gate and photodiode optimization method for CMOS Image sensors are described in this paper, which enables the design of large-scale ultra-high-speed burst mode CMOS Image sensors in a low-cost standard CMOS Image sensor process without the need for process customization or advanced process. The sequential transfer gates also show a clear advantage in minimizing the floating diffusion capacitance and improving image sensor conversion gain in large-scale pixels.
A reset noise reduction method using a feedback amplifier that results in an 80% noise reduction in 3-transistor (3-T) pixels is presented. 3-T pixels are useful for non-visible imaging applications because they have fewer post-processing issues than 4-T pixels and do not require charge transfer. They suffer from reset noise because correlated-double sampling cannot be realized without additional memory. Analysis of the experimental power spectral density indicates potential for further noise cancellation in future devices.