The cameras are invented by imitating the human visual system to capture the scene. The camera
technologies have been substantially advanced in recent years. 108 MP resolution with 100x hybrid
zoom has become standard features for smartphone flagships. In spite of the recent developments, the
cameras are still restricted in terms of FoV, depth perception, pixel size, lens system, and more.
That is why multicamera systems have progressively become prevalent. The multicamera systems can be a remedy to overcome the limitations that single cameras hold. The FoV can be raised to $360^\circ$
through image stitching. The depth can be computed by stereo matching methods. The lens flaws and
imperfections can be handled thanks to computer vision and image processing algorithms. Significant
computational power is required to process a vast amount of pixels coming from multiple cameras. GPU
and FPGA are promising platforms to implement computer vision and video processing applications due
to their sophisticated parallelization features. FPGA platforms present more prevailing features,
especially for real-time and portable vision applications. FPGAs provide less latency as they hold
the connection to image sensors from a low level. FPGA enables the implementation of a system
architecture dedicated to the target application. The compact systems can be designed by designing
custom PCBs using only necessary ports. Also, FPGAs consume lower power and cheaper option compared to GPUs. On the other hand, GPUs propose more versatility and easy design and upgrade time. In the
light of these observations, software and hardware integrated real-time high-resolution multi-view
3D and panoramic systems are presented in the scope of this thesis.

Firstly, the depth estimation system is presented in the first part of the thesis. The proposed
depth estimation system runs in real-time performance for up to 2K depth map resolution. The system
adopts the trinocular scheme to address the occlusion problem. The pixel correspondence challenge in
textureless-regions, from which the conventional stereo matching-based depth estimation systems
suffer, is tackled by projecting artificial patterns through the integrated pico-projector. The
application-specific system architecture ensures the high-performance depth map streaming.

Secondly, the drone detection and tracking system is presented. The proposed drone detection system
is capable of simultaneously monitoring 360° environment and detecting the drone from a
long-range in real-time performance. The distributed architecture design enables
ultra-high-resolution image processing.
data coming from the hardware part. The GPU design is opted due to its high level of parallelization
capability. The proposed system is appropriate to be employed for surveillance applications such as
drone detection, passive radar system, vast terrain, and border control applications.

Thirdly, the 3D stereoscopic panorama construction system is presented. The proposed system
generated 2 separate panoramas for the left and right eyes to achieve 3D perception. The system
offers the novel camera arrangement and the 3D panorama generation algorithm. The cameras are
positioned to minimize the intra-panorama parallax while raising the inter-panorama parallax to
augment 3D perception.

Finally, the real-time vision systems are discussed with their pros and cons, and future predictions
are presented in the conclusion part of the thesis.