  The existing lensless compressive camera
($\text{L}^2\text{C}^2$)~\cite{Huang13ICIP} suffers from low capture rates,
resulting in low resolution images when acquired over a short time. In this
work, we propose a new regime to mitigate these drawbacks. We replace the
global-based compressive sensing used in the existing $\text{L}^2\text{C}^2$ by
the local block (patch) based compressive sensing. We use a single sensor for
each block, rather than for the entire image, thus forming a multiple but
spatially parallel sensor $\text{L}^2\text{C}^2$. This new camera retains the
advantages of existing $\text{L}^2\text{C}^2$ while leading to the following
additional benefits: 1) Since each block can be very small, {\em e.g.}$~8\times
8$ pixels, we only need to capture $\sim 10$ measurements to achieve reasonable
reconstruction. Therefore the capture time can be reduced significantly. 2) The
coding patterns used in each block can be the same, therefore the sensing
matrix is only of the block size compared to the entire image size in existing
$\text{L}^2\text{C}^2$. This saves the memory requirement of the sensing matrix
as well as speeds up the reconstruction. 3) Patch based image reconstruction is
fast and since real time stitching algorithms exist, we can perform real time
reconstruction. 4) These small blocks can be integrated to any desirable
number, leading to ultra high resolution images while retaining fast capture
rate and fast reconstruction. We develop multiple geometries of this block-wise
$\text{L}^2\text{C}^2$ in this paper. We have built prototypes of the proposed
block-wise $\text{L}^2\text{C}^2$ and demonstrated excellent results of real
data.
